Insolvency proceedings are a situation that concerns many companies, especially when they start accumulating debt, payment delays or treasury pressure. However, entering insolvency proceedings does not always mean the immediate closure of the business.

In many cases, this procedure can help organise debts, protect business activity and seek a viable solution with creditors. The key is to act in time, analyse the financial situation properly and rely on specialised advice.

What are insolvency proceedings?

To understand what insolvency proceedings are, it is useful to start with a simple idea: they are a legal procedure that is activated when a company, self-employed professional or individual cannot regularly meet their payment obligations.

Their purpose is to organise the insolvency situation, protect creditors’ rights and assess whether there is a real possibility of continuity. If the company is viable, an agreement may be sought. If it is not, the procedure may end in liquidation.

For this reason, insolvency proceedings should not be seen only as the end of a company, but as a legal route to organise a complex economic situation.

When a company enters insolvency proceedings, the process becomes subject to court supervision. From that moment on, debts, assets, creditors, business viability and possible solutions are analysed.

This may involve changes in company management, limitations on certain decisions and greater oversight of financial operations. Even so, the company can continue operating if there is activity and a real possibility of continuity.

Types of insolvency proceedings

There are different types of insolvency proceedings, depending on who requests them and the situation the company is in.

Voluntary insolvency proceedings are usually more advisable when the company detects the problem in time, as they allow it to anticipate the situation and show a more organised attitude towards insolvency.

What happens if my company enters insolvency proceedings?

One of the most common questions is: what happens if my company enters insolvency proceedings? The answer depends on the financial situation, the level of debt and whether the business remains viable.

In general terms, several things can happen:

• Certain debt claims are suspended or reorganised.
• All creditors are identified.
• The company’s assets are analysed.
• Whether activity can continue is reviewed.
• Possible payment agreements are studied.
• An insolvency administrator may be appointed.
• It is assessed whether an agreement or liquidation is appropriate.

Insolvency proceedings should not be understood only as a failure, but as a mechanism to organise a critical situation. In some cases, they allow the company to gain time, negotiate with creditors and avoid rushed decisions.

How insolvency proceedings work

Insolvency proceedings usually follow several stages, although they may vary depending on the specific case and the type of debtor.

1. Situation analysis

Before filing for insolvency proceedings, it is important to review the debt, treasury position, contracts, assets, pending payments and business viability. At this stage, good business financial planning can help anticipate scenarios, organise priorities and make decisions with greater control.

2. Filing for insolvency proceedings

The request can be filed by the company itself or by a creditor. When insolvency is already real, it is important to act quickly and not wait for the situation to worsen.

Filing for insolvency proceedings on time can facilitate a more organised management of the process and reduce the risk of making rushed decisions.

3. Court declaration

The court analyses the request and, if the requirements are met, declares the insolvency proceedings. From that point, the procedure formally begins and the situation with creditors is organised.

At this stage, the financial documentation, asset situation and the company’s ability to continue operating are reviewed.

4. Insolvency administrator

In certain cases, an insolvency administrator is appointed to supervise the financial situation, review documentation and participate in the management of the procedure.

Their role is to help organise the information, assess the company’s real situation and protect the interests of the parties involved.

5. Report, inventory and list of creditors

During the procedure, the company’s assets, rights, debts and creditors are identified. This part is essential to understand what is owed, who it is owed to and what resources are available.

It is also important to have clear and updated financial information. Financial consolidation solutions make it possible to obtain a more accurate view of the financial situation, especially in companies with several entities, subsidiaries or complex structures.

6. Agreement or liquidation

If the company is viable, it may try to reach an agreement with creditors. This agreement may include payment extensions, debt reductions or new payment conditions.

If there is no real possibility of continuity, the procedure may end in liquidation.

Liquidation in insolvency proceedings

Liquidation in insolvency proceedings occurs when it is not possible to maintain activity or when no viable solution is approved to pay the debts. In that case, the company’s assets are sold to pay creditors according to the established order.

Liquidation may mean the closure of the company, but it can also help organise the end of activity and prevent the situation from deteriorating further.

This stage is not always reached. If the company acts in time and has a viable model, alternatives such as agreements, debt restructuring, sale of productive units or continuity with adjustments may be considered.

In some cases, when the company retains assets, customers or a viable productive unit, corporate transactions such as a business merger may also be assessed to preserve part of the activity or integrate it into a stronger structure.

Can a company exit insolvency proceedings?

Yes, it is possible to exit insolvency proceedings, but it will depend on the company’s real situation. A company with temporary liquidity problems is not the same as a company with no activity, no revenue and no ability to generate cash.

Some ways to overcome insolvency proceedings include:

• Reaching an agreement with creditors.
• Restructuring debt.
• Reducing costs and reorganising activity.
• Selling non-strategic assets.
• Maintaining the productive unit if the business is viable.
• Improving financial management and payment planning.

Exiting insolvency proceedings requires a realistic plan. It is not enough to postpone payments; the company must show that it can generate enough income to meet its future commitments.

How to overcome insolvency proceedings

To overcome insolvency proceedings, the most important thing is to act quickly and not wait until the situation becomes irreversible.

Some key recommendations are:

• Review the financial situation as soon as possible.
• Have a clear treasury forecast.
• Identify which debts are most urgent.
• Analyse whether the business remains viable.
• Negotiate with creditors before the conflict increases.
• Prepare accounting and financial documentation.
• Avoid new debts that worsen the situation.
• Rely on specialised legal and financial advice.

The sooner the problem is detected, the more options there are to preserve activity, negotiate payments and avoid liquidation.

Common mistakes when entering insolvency proceedings

Some mistakes can worsen the company’s situation and reduce its chances of recovery:

• Waiting too long to act.
• Hiding financial information.
• Continuing to accumulate debt without a clear plan.
• Not speaking with creditors.
• Confusing a temporary lack of liquidity with structural insolvency.
• Not preparing the documentation properly.
• Making decisions without advice.
• Thinking that insolvency proceedings always mean closure.

Entering insolvency proceedings does not have to mean the end of a company. It can be a tool to organise debt, protect activity and seek a viable way forward. The difference usually lies in acting in time, analysing the numbers realistically and making decisions before the situation becomes impossible to redirect.

La entrada Insolvency proceedings: what they are and how to overcome them se publicó primero en Acevedo.

What does it mean to modernise an on-premise infrastructure?

Modernising an on-premise infrastructure means updating the systems, servers, applications and technology processes that still depend on physical or local resources, so they can respond better to current business needs. It does not always mean completely abandoning the company’s own environment or moving everything to the cloud, but rather reviewing which part of the infrastructure should be maintained, which part can be optimised and which workloads should move to a cloud or hybrid model.

In many companies, on-premise solutions remain critical because they support key operations, sensitive data or applications that cannot be changed overnight. The problem appears when that infrastructure starts generating high costs, rigidity, integration difficulties, performance issues or continuity risks. At that point, modernisation stops being a technical improvement and becomes a strategic decision.

A well-planned modernisation helps reduce dependence on obsolete hardware, improve security, make scaling easier, connect systems more effectively and prepare the organisation for new digital tools. The goal is not to move everything to the cloud just because it is fashionable, but to build a more flexible, secure and sustainable infrastructure aligned with the company’s operational reality.

Signs that your on-premise infrastructure has become obsolete

An on-premise infrastructure does not become obsolete simply because the cloud exists, but when it starts to limit operations, increase maintenance costs or prevent the company from evolving with agility. Many organisations live for years with servers, applications and on-premise solutions that still work, but require more and more effort to maintain, integrate or scale.

Increasingly high maintenance costs

One of the clearest signs is that maintaining the infrastructure is becoming increasingly expensive. This can include server renewal, storage expansion, licences, specialised support, energy consumption, physical space and technical team hours. When a large part of the budget is allocated to keeping old systems running instead of improving capabilities, the infrastructure starts to become a brake on the business.

Scalability and performance problems

On-premise infrastructures depend on installed capacity. If the company needs more resources, it usually has to buy, configure and deploy new hardware, which slows down the response to changes in demand. This can be seen in slow systems, occasional outages, saturation at critical moments or difficulty growing without new investments.

Difficulty integrating new solutions

Another common sign is that connecting the current infrastructure with new tools becomes complex. Integrating cloud solutions, SaaS applications, ERPs, CRMs, analytics or automation platforms may require custom developments, fragile connections or manual processes. The result is often scattered information, duplicated data and little ability to work with a unified view of the business.

Security, support and continuity risks

When systems become outdated, unsupported by the manufacturer or difficult to patch, the risk of vulnerabilities and failures increases. In addition, if incident recovery depends on manual processes or old infrastructures, any outage can directly affect business continuity. Modernisation makes it possible to reduce exposure, improve data protection and strengthen recovery capacity.

On-premise, cloud or hybrid model: key differences

Choosing between on-premise, cloud or hybrid infrastructure does not depend only on technology, but on what the company needs to protect, scale and control. Each model offers a different balance between investment, flexibility, security, maintenance and growth capacity. That is why, before modernising, it is important to understand what each option provides and in which scenarios it fits best.

On-premise infrastructure

On-premise infrastructure is based on servers, storage, networks and applications hosted on the company’s premises or in a directly controlled environment. Its main advantage is the level of control over data, configuration and security, which is important in regulated sectors or with very strict internal requirements. In return, it requires more investment in hardware, maintenance, updates, technical staff and failure recovery capacity.

Cloud infrastructure

Cloud infrastructure allows companies to consume technology resources from an external provider, under a flexible and scalable model. Instead of buying and maintaining their own servers, companies can increase or reduce capacity according to their needs, access advanced services and delegate part of the maintenance, security and updates. It is especially useful when the objective is agility, availability and less dependence on physical infrastructure.

Hybrid infrastructure

Hybrid infrastructure combines on-premise and cloud environments within the same technology strategy. It allows companies to keep the most critical, sensitive or difficult-to-migrate systems locally, while moving other workloads, applications or services that need more flexibility to the cloud. This model is often the most realistic option for companies with legacy systems, because it enables progressive modernisation without putting operational continuity at risk.

When it makes sense to migrate to the cloud

It makes sense to migrate to the cloud when the current infrastructure needs more flexibility, scalability and adaptability than an on-premise environment can provide. It is especially recommended if the company has demand peaks, needs to deploy new services quickly, wants to reduce internal maintenance workload or seeks access to more advanced technologies without constantly investing in its own hardware.

It also makes sense when systems must be available from different locations, when the business is growing quickly or when local infrastructure has become a fixed cost that is difficult to justify. In these cases, the cloud allows the company to move to a more flexible model, where resources are better adjusted to the real needs of each moment.

When it makes sense to keep on-premise solutions

Keeping on-premise solutions may still be appropriate when there are very strict requirements for control, security, latency or regulatory compliance. Some companies need to keep certain data, applications or critical workloads in their own environments because their sector, internal policy or the nature of their operations requires it.

It may also make sense when an application works correctly, is deeply integrated with internal systems or migrating it would involve more risk than benefit. In these cases, modernisation does not necessarily mean moving everything to the cloud, but optimising what already exists, strengthening security, improving performance and ensuring continuity.

When to choose a hybrid infrastructure

Hybrid infrastructure is often the most balanced option when the company needs to modernise without disrupting operations. It allows critical or more sensitive systems to remain local, while moving to the cloud those workloads that require more scalability, availability or ease of integration.

This approach fits especially well in organisations with legacy systems, complex dependencies or processes that cannot be migrated all at once. With a hybrid model, the company can move forward in phases, reduce risks and take advantage of the benefits of the cloud without giving up control over certain technology assets.

How to approach infrastructure modernisation without putting operations at risk

Modernising an infrastructure should not be approached as a sudden change, but as a controlled process. Before moving workloads, replacing systems or incorporating cloud services, it is necessary to understand what exists, what depends on what and what impact any change would have on the company’s daily activity. The goal is to move towards a more flexible and secure infrastructure without causing unnecessary interruptions.

Evaluate systems, workloads and dependencies

The first step is to analyse the current infrastructure: servers, applications, databases, networks, integrations, users and associated processes. This assessment makes it possible to identify which systems are critical, which workloads consume the most resources, which technologies are obsolete and which dependencies could create problems during a migration or update.

Without this diagnosis, any decision is made blindly. An application may seem simple to move, but it may depend on an old database, a specific integration or an internal process that affects the entire project.

Prioritise critical applications and processes

Not everything should be modernised at the same time. It is advisable to classify applications according to their importance for the business, their technical complexity and the risk involved in changing them. The most critical systems require more careful planning, prior testing and clear contingency plans.

In many cases, the best approach is to start with less sensitive workloads or with processes where the benefit is high and the risk is acceptable. This allows visible improvements to be achieved without compromising operational continuity.

Define a phased roadmap

Modernisation should move forward in stages: assessment, design, testing, partial migration, validation and scaling. This roadmap makes it possible to control the impact of each change, correct deviations and avoid making the project depend on one large migration.

Working in phases also makes it easier to combine models. A company can keep certain on-premise solutions, move others to the cloud and progressively build a hybrid architecture according to its priorities and restrictions.

Monitor performance, costs and security

Once modernisation has started, it is essential to continuously measure the behaviour of the new infrastructure. Performance, availability, resource consumption, cloud costs, security alerts and user experience must all be reviewed.

This monitoring makes it possible to verify whether modernisation is meeting its objectives and detect problems before they affect the business. Modernisation does not end with migration or an architecture change: it requires follow-up, adjustment and continuous improvement to ensure the infrastructure remains efficient, secure and sustainable.

La entrada Modernising on-premise infrastructure: when to migrate to the cloud or choose a hybrid model se publicó primero en Acevedo.

Subsidiary companies are a common option for businesses that want to grow, enter new markets or separate different lines of business. This model allows a parent company to control another company while maintaining a separate legal and operational structure. It is important when a company wants to expand, reorganise its activity or create an independent entity to operate in another country or sector.

What is a subsidiary company?

A subsidiary company is a company that is wholly or partially owned by another company, known as the parent company. The parent company has a controlling stake in the subsidiary and can influence its strategic, financial and operational decisions.

The subsidiary has its own legal personality. This means it can have its own name, management, tax obligations, contracts, accounting and legal responsibilities.

For example, an international company may create a subsidiary in Spain to sell its products, hire local staff and operate under Spanish regulations, while the parent company maintains overall control of the business.

Difference between subsidiary company, affiliate and branch

The terms subsidiary and affiliate are often used in a similar way, as both refer to a company controlled by a parent company. The most important difference is usually between a subsidiary and a branch.

The difference matters because it affects legal liability, taxation, accounting and day-to-day management.

What is a subsidiary company used for?

Creating a subsidiary company can make sense when a company wants to grow with a more organised structure.

Some common uses include:

• Entering a new country or market.
• Separating a line of business.
• Protecting the parent company from certain risks.
• Managing independent brands or projects.
• Facilitating investment or acquisition operations.
• Adapting better to local regulations.
• Organising the group’s financial information more effectively.

For example, a company that wants to expand internationally may create a subsidiary to operate in the target country through its own legal entity.

Advantages of creating a subsidiary company

One of the main advantages of a subsidiary is that it allows different activities to be legally separated. This can help limit risks, organise management more effectively and make it easier to control each business unit.

It can also be useful for international expansion, as the company can operate as a local entity and adapt better to the market, taxation and regulations of the country.

Main advantages include:

• Greater legal separation between activities.
• Better risk control.
• Possibility of operating in new markets.
• Differentiated management by country or business line.
• Better tax and operational adaptation.
• Greater financial control within the group.

When a company manages several entities, it is important to have financial consolidation tools that allow data to be unified and the group’s overall performance to be analysed.

Challenges of a subsidiary company

Although a subsidiary can bring many advantages, it also involves more management. Creating a new company means assuming tax, accounting, legal and administrative obligations.

Some common challenges include:

• Greater accounting complexity.
• Incorporation and maintenance costs.
• Need to comply with local regulations.
• More financial reporting.
• Coordination between parent company and subsidiary.
• Management of taxes, contracts and documentation.

That is why, before opening a subsidiary, it is advisable to analyse whether it is really the best option or whether a branch, a local partnership or another simpler formula may be sufficient.

How to open a subsidiary company

Knowing how to open a subsidiary company depends on the country where it will operate, although the process usually follows a series of common steps.

1. Define the purpose of the subsidiary

Before starting the formal procedures, the parent company must be clear about why it wants to create the subsidiary. Opening a company to sell in another country is not the same as doing so to separate a business line or launch a new brand.

At this stage, it is advisable to define the market, the required investment, the team, the risks and the financial objectives. Good business financial planning helps assess whether the new company will be viable.

2. Choose the legal form

The next step is to choose the most appropriate legal form. In Spain, many subsidiaries are incorporated as a Limited Liability Company or a Public Limited Company, depending on the size of the project, the capital and the shareholder structure.

3. Prepare the documentation

After that, the necessary documentation must be prepared: company name, articles of association, shareholder details, share capital, registered address and corporate purpose.

The articles of association must define how the company will operate, what activity it will carry out and how its management will be organised.

4. Incorporate the company

The incorporation is usually formalised before a notary through a public deed. After that, the company must be registered with the Commercial Registry and obtain its tax ID number in order to operate.

It will also be necessary to complete the corresponding tax, employment and administrative procedures before starting activity.

Examples of subsidiary companies

A simple example would be a foreign technology company that creates a subsidiary in Spain to sell its solutions, hire a local team and invoice Spanish customers.

Another case would be a business group that decides to separate its logistics division into its own company. This allows it to better control costs, staff, assets and results for that specific line.

It can also happen when a company acquires another company and keeps it as a subsidiary within the group. In these cases, the parent company controls the acquired company, but may keep its brand, team and operations.

In growth or integration operations, a business merger can also be analysed when the objective is not to maintain separate companies, but to combine structures.

Financial management of a subsidiary company

Once the subsidiary has been created, the parent company needs to control the financial information, costs, results and evolution of each company within the group.

This is especially important when there are several subsidiaries in different countries, currencies or tax frameworks. In these cases, having integrated systems helps reduce errors, improve visibility and make decisions with updated data.

An ERP or business management solution can facilitate the connection between the parent company and its subsidiaries, centralising finance, purchasing, sales, inventory, reporting and operational processes.

What to consider before opening a subsidiary

Before opening a subsidiary company, it is advisable to review some key points:

The key is not to create a subsidiary only for structural reasons, but because it brings a real advantage to the business.

Common mistakes when creating a subsidiary company

Some mistakes can complicate the creation and management of a subsidiary:

• Opening the company without a clear strategy.
• Not properly analysing tax and legal obligations.
• Choosing an unsuitable legal form.
• Not defining the relationship between parent company and subsidiary.
• Duplicating unnecessary processes.
• Not having integrated financial reporting.
• Not assessing maintenance costs.
• Treating the subsidiary as a simple delegation.

A subsidiary company can be a very useful tool to grow, enter new markets or separate activities. The key is to define its purpose properly, choose the right structure and have systems that allow financial and operational information to be controlled from the start.

La entrada Subsidiary companies: what they are, how to open one and examples se publicó primero en Acevedo.

Scaling a startup is not only about selling more, hiring more people or entering new markets. A company can grow in revenue and still not be truly scalable if every new customer means more costs, more operational workload and more internal complexity.

The key is to ensure that the business can increase revenue, customers and market presence without the required resources growing at the same pace. That is why, before asking how to scale my startup, it is important to analyse whether the business model, processes, technology and team are prepared to grow sustainably.

Although there are many ways to scale a business, in the case of a startup the challenge is doing so without losing agility, financial control or adaptability.

What does it mean to scale a startup?

Scaling a startup means increasing business volume while maintaining efficiency. In other words, growing without always depending on more working hours, more people or proportional investment.

A scalable startup is one that can repeat its model across different customers, markets or segments without having to rebuild its processes from scratch. To achieve this, it needs a clear value proposition, measurable acquisition channels, defined internal processes and a technology structure capable of supporting growth.

The difference between growing and scaling lies in profitability. Growing can mean selling more. Scaling means selling more while keeping costs and operations under control.

What makes a startup scalable?

To understand what makes a startup scalable, several elements of the business must be reviewed.

First, there must be a repeatable model. If every customer needs a fully customised solution, it will be difficult to increase volume without increasing costs. On the other hand, if the product or service can be delivered in a similar way in many cases, the startup will have greater growth capacity.

It is also important that costs do not increase at the same pace as revenue. Automation, technology and process improvement allow the team to manage more customers without multiplying the internal structure.

In addition, a scalable startup needs predictable acquisition channels. It is not enough to win customers occasionally. It is necessary to know how much it costs to acquire a customer, what return that customer generates and which channels have the greatest growth potential.

How to scale a startup step by step

1. Validate the market before growing

Before scaling, the startup must confirm that there is a real need in the market. This means validating that customers understand the value proposition, are willing to pay and continue using the product or service after the first purchase.

Positive signs include repeat purchases, recommendations, good customer retention and clear feedback on the value provided by the solution.

Scaling without validating the market can lead to cash flow problems, dissatisfied customers and an operation that is difficult to sustain.

2. Analyse your key metrics

A startup should not scale without knowing its numbers. Revenue is important, but it is not enough to know whether the business is sustainable. Some key metrics are:

If revenue increases but costs grow at the same pace or faster, the startup is not scaling correctly. That is why good business financial planning helps control investment, anticipate needs and make better decisions before accelerating growth.

3. Automate repetitive processes

Automation is one of the keys to scaling. A startup that depends too much on manual tasks will have more difficulty growing without increasing costs.

Some processes that can be automated are:

• Welcome emails.
• Sales follow-up.
• Lead management.
• Invoicing.
• Reports.
• Internal reminders.
• Initial customer support.
• Contact segmentation.

Automating does not mean losing closeness with the customer. It means freeing up the team’s time so they can focus on higher-value tasks.

At this point, it may be useful to review how artificial intelligence helps scale a business with AI, especially when there are repetitive processes, manual tasks or large volumes of data.

More advanced solutions can also come into play, such as AI agents, which make it possible to execute tasks, analyse information and support decision-making across different business processes.

4. Standardise the way of working

In the early stages, many startups work with informal processes because the team is small. However, when customers, sales and tasks increase, that improvisation can become a problem.

To scale, it is advisable to document processes such as:

• Customer acquisition.
• Opportunity qualification.
• Onboarding.
• Product or service delivery.
• Support.
• Incident management.
• Metric tracking.

Having clear processes allows growth not to depend only on a few people and makes it easier for the team to work in a more organised way.

5. Build profitable acquisition channels

To scale a startup, acquisition must be measurable and sustainable. It is not just about attracting more leads, but about acquiring profitable customers.

Channels can include SEO, Ads, content, email marketing, partners, referrals or outbound sales. The important thing is to identify which ones have the best conversion, the lowest acquisition cost and the greatest growth potential.

Depending on a single channel can be risky. That is why a scalable strategy usually combines several channels and measures the performance of each one.

6. Prepare the team to grow

Scaling also means organising the internal structure. It is not always about hiring more people, but about defining responsibilities more clearly.

Each person must know what decisions they can make, which processes they lead and how their work is measured. This avoids bottlenecks and allows the startup to grow without losing agility.

At this stage, it may also be useful to outsource tasks that are not part of the core business, especially if this helps maintain a more flexible structure.

How to measure startup scalability

To know how to measure the scalability of a startup, it is advisable to analyse different areas of the business:

If every new customer generates too much internal workload, too many costs or too many incidents, the startup still needs to improve its foundation before scaling.

When to consider expansion into new markets

Once the model works, the startup can consider growing into new segments, regions or countries. However, expansion must be based on prior analysis.

Before taking the step, it is advisable to study the market size, competition, legal requirements, entry costs and internal capacity to serve new demand.

If the startup already has solid processes and a validated model, it can assess strategies to expand a business internationally without losing operational control.

Common mistakes when scaling a startup

Some common mistakes are:

• Scaling before validating the product.
• Hiring without having clear processes.
• Not measuring customer acquisition cost.
• Depending on a single acquisition channel.
• Automating without taking care of the user experience.
• Growing revenue without reviewing profitability.
• Expanding into new markets too early.

Knowing how to scale a startup involves much more than selling more. A scalable startup needs a repeatable model, clear processes, technology, profitable acquisition channels and metrics that allow decisions to be made with data.

Before accelerating growth, it is important to review whether the product is validated, whether the numbers are sustainable and whether the team can take on more volume without losing quality.

Scaling well is not about growing fast at any cost, but about building a solid foundation to increase revenue, customers and market reach without losing control.

La entrada How to scale a startup se publicó primero en Acevedo.

When a company is really in crisis

A company is really in crisis when its problems stop being isolated and start compromising its liquidity, profitability, ability to pay or operational continuity. It is not just about selling less during a specific period, but about accumulating signs that show the business is not generating enough resources, is not controlling its costs properly or does not have reliable information to make decisions on time.

Liquidity problems and accumulated debt

Lack of liquidity is one of the clearest signs of a company in crisis. There may be sales, customers and even business activity, but if there is not enough cash to meet current payments, the company starts to lose its ability to react. Delays with suppliers, payroll, taxes or loans usually indicate that the problem is no longer just a treasury issue, but a matter of financial balance.

When debt accumulates and short-term financing is used to cover recurring expenses, the business enters a dangerous dynamic. Each maturity date reduces room for manoeuvre and forces increasingly urgent decisions.

Falling sales or loss of key customers

A sustained drop in sales may be caused by market changes, loss of competitiveness, lower demand or a value proposition that no longer works. The problem becomes more serious when the company depends on a small number of customers and loses one of them, because the impact on revenue can be immediate.

In these cases, it is not enough to wait for the market to improve. It is necessary to analyse which products, services, channels or customers remain profitable and which ones are weakening the stability of the business.

High costs and low profitability

A company can be in crisis even if it continues to invoice if its costs consume most of its margin. Oversized structures, inefficient processes, poorly negotiated purchases or unprofitable business lines can mean that sales growth does not translate into profit.

When profitability falls repeatedly, the company starts financing its inefficiencies through debt, delayed payments or reduced investment. This situation ultimately affects service quality, the team and the ability to compete.

Lack of financial and operational control

A crisis can also appear when management does not have reliable data to understand what is happening. If there is no clear information on available cash, overdue debt, margins by business line, real costs or forecasts, decisions are made late and with too much uncertainty.

Lack of financial and operational control prevents problems from being detected in time. That is why many companies do not react until the situation is already serious, when the room to negotiate, reorganise or recover the business is much smaller.

How to recover a company in crisis step by step

Recovering a company in crisis requires acting with order and speed, but without making improvised decisions. The first objective is to understand the real situation of the business, protect liquidity and separate what is urgent from what is important. From there, recovery must be based on specific measures: adjusting costs, renegotiating commitments, reorganising processes and defining a recovery plan with measurable objectives.

Analyse the real financial situation

The first step is to know exactly where the company stands. This means reviewing available cash, overdue debt, upcoming payments, expected collections, margins by product or service and the real evolution of income and expenses. Without this diagnosis, any measure may end up being only a temporary fix.

This analysis must answer basic questions: how much money comes in, how much goes out, which payments are urgent, which areas generate losses and what room exists for negotiation. The clearer the information, the easier it will be to prioritise decisions and avoid impulsive moves.

Review expenses, margins and unprofitable business lines

A company in crisis cannot afford to maintain costs that add no value or business lines that consume resources without generating profitability. Reviewing expenses does not mean cutting without criteria, but identifying which costs are essential, which can be reduced and which activities are weakening the overall result.

It is also important to analyse real margins. Sometimes the problem is not selling too little, but selling products or services that leave little profit, require too much operational effort or create cash flow pressure. Detecting this makes it possible to focus resources on what truly sustains the business.

Renegotiate debt, payments and outstanding commitments

When there is liquidity pressure, renegotiation is a key measure. This may include extending payment terms with suppliers, reviewing conditions with banks, postponing certain commitments or seeking agreements with creditors before the situation deteriorates further.

Renegotiation must be done with data and with a credible plan. It is not just about asking for more time, but about showing that the company is taking measures to recover stability. The sooner action is taken, the more options there will be to reach reasonable agreements.

Reorganise processes and business priorities

In a crisis, the company must focus on what is essential. This means reviewing internal processes, eliminating duplicated tasks, reducing inefficiencies and prioritising the activities that generate cash, customers or strategic value. Maintaining the same structure that led to the problem often prevents recovery.

Reorganisation may also require changes in teams, responsibilities, suppliers, sales channels or ways of working. The goal is for the business to become more agile, more profitable and less dependent on processes that consume time and resources without delivering results.

Define a recovery plan with clear objectives

Recovery needs a concrete plan, not just good intentions. That plan must include financial, commercial and operational measures, with owners, deadlines and monitoring indicators. It must also distinguish between immediate actions to gain liquidity and medium-term decisions to recover profitability.

A good recovery plan makes it possible to measure whether the company is improving or continuing to deteriorate. Without clear objectives, it is easy to confuse activity with progress. That is why each measure must be linked to specific results: debt reduction, cash improvement, margin growth, sales recovery or elimination of losses.

Business turnaround: what measures can help

A business turnaround is not just about cutting costs or obtaining short-term financing. To recover a company in crisis, it is necessary to combine financial, operational and strategic measures that help gain liquidity, improve profitability and regain control over the evolution of the business. The key is to act on the real causes of the crisis, not only on its symptoms.

Financial restructuring

Financial restructuring aims to relieve the company’s economic pressure and recover stability. It may include renegotiating debt, extending payment terms, refinancing loans, selling non-strategic assets or reaching new agreements with creditors.

This measure is especially important when the company has activity and potential, but is under pressure from maturities, interest or accumulated commitments. Restructuring does not mean postponing the problem, but organising financial obligations so the business can continue operating and recover.

Cost and operations optimisation

Optimising costs does not mean cutting indiscriminately. A company in crisis needs to distinguish between necessary expenses, unnecessary expenses and inefficiencies that are reducing profitability. It must also review internal processes, purchases, suppliers, staff structure, logistics and tasks that consume resources without adding value.

The aim is to build a lighter and more efficient operation, capable of generating better results with less friction. When done properly, optimisation helps reduce pressure on cash flow without damaging commercial capacity or service quality.

Business model review

In some cases, the crisis is not only caused by a financial problem, but by a business model that has stopped working. There may be unprofitable products, customers that consume too much margin, dependence on a specific channel or a value proposition that no longer responds to the market.

Reviewing the business model makes it possible to decide what to keep, what to change and what to abandon. This measure helps focus resources on the lines with the greatest potential and prevents the company from continuing to invest in activities with no future path.

Improved control and indicator tracking

Without reliable indicators, recovery becomes guesswork. To turn a company around, it is essential to continuously measure liquidity, debt, margins, sales evolution, profitability by business line and compliance with the recovery plan.

Having updated data makes it possible to detect deviations early, correct decisions and check whether the measures are working. In a company in crisis, speed of reaction depends directly on the quality of the available information.

Options when the business crisis is more serious

When the crisis already compromises the company’s viability, reducing costs or improving internal management is no longer enough. At that point, it is advisable to assess more structured mechanisms to organise debt, protect activity and prevent the situation from progressing without control. The right option will depend on the level of insolvency, the real capacity for recovery and the room for negotiation with creditors.

Restructuring plan

A restructuring plan allows the company to reorganise its debt and commitments before reaching an irreversible situation. It may include debt reductions, extensions, refinancing, changes in maturities, asset sales or operational measures to recover viability.

It is a useful tool when the company still has activity, customers and the capacity to generate income, but needs to gain time and organise its financial obligations to prevent debt pressure from blocking recovery.

Insolvency proceedings

Insolvency proceedings are a legal procedure for companies that cannot regularly meet their payments. Although they are often perceived as a last resort, they may be necessary when insolvency is already serious and there is not enough room for private agreements.

Their purpose is to organise the relationship with creditors, protect certain interests and seek a viable outcome, either through an agreement, restructuring or liquidation if there is no real possibility of continuity.

Specialised financial and legal advice

In an advanced crisis, specialised advice is key to avoiding late or disorderly decisions. A financial analysis makes it possible to understand the real viability of the business, while legal support helps choose the right mechanism and avoid risks for directors, partners or creditors.

The combination of financial and legal insight allows the company to act with greater security, prioritise measures and negotiate from a stronger position.

Mistakes that can worsen a company in crisis

In a company in crisis, acting late or making decisions without data can accelerate deterioration. Many problems get worse not only because of falling sales or lack of liquidity, but because of improvised responses that consume time, resources and trust. Avoiding these mistakes is just as important as applying recovery measures.

Common mistakes:

• Denying the seriousness of the situation and waiting for the problem to solve itself.
• Making decisions without updated financial information, especially regarding cash, debt and margins.
• Cutting costs without clear criteria, affecting areas that do generate value or revenue.
• Continuing to finance unprofitable business lines out of inertia or fear of change.
• Delaying negotiation with banks, suppliers or creditors until there is no room left.
• Failing to communicate the plan internally, creating uncertainty and loss of trust in the team.
• Confusing turnover with profitability, maintaining customers or projects that consume margin.
• Not asking for specialised help in time, especially when there are debt, insolvency or legal risk issues.

When to ask for help to recover a company in crisis

It is advisable to ask for help when the company no longer has a clear view of its financial situation or when internal measures are not producing results. If liquidity is shrinking, debt is growing, payments are delayed or the management team does not know which decisions to prioritise, external support can make the difference between reacting in time or losing room for manoeuvre.

It is also advisable to seek advice when the crisis affects banks, suppliers, creditors, partners or employees. In these cases, decisions have financial, operational and legal implications, so they should not be made in isolation.

Asking for help does not mean assuming the company has no way out. On the contrary, it is often the first step towards organising the information, identifying real options and building a viable recovery plan before the situation becomes irreversible.

La entrada How to move a company in crisis forward se publicó primero en Acevedo.

Accelerating the financial close does not depend on working longer hours, but on reducing manual workload, centralising information and automating the tasks that cause the most delays. When reconciliations, adjustments, approvals and reports depend on spreadsheets and scattered validations, the close becomes slow, unreliable and difficult to audit. Modernising the process makes it possible to close earlier, with fewer errors, greater traceability and more useful financial data for management, turning the close into a tool for control and decision-making, not just a repetitive month-end task.

Why the financial close becomes slow and unreliable

The financial close becomes slow when the team depends on spreadsheets, manual validations, emails, scattered data and last-minute adjustments to balance the information for the period. The problem is rarely a single task, but rather the accumulation of small frictions: data arriving late, reconciliations reviewed by hand, duplicated file versions, unclear ownership and lack of visibility into the real status of the close.

When the process works this way, the close not only takes longer, it also becomes less reliable. Each manual review increases the risk of error, each change without traceability makes auditing more difficult and each outdated figure reduces management’s confidence in the final reports. That is why accelerating the financial close is not just about “working faster”, but about reducing manual dependencies and building a more controlled, repeatable and traceable process.

Which tasks should be automated to close faster

To accelerate the financial close, the most effective approach is not to automate everything at once, but to start with the tasks that consume the most time, generate the most errors and block the team’s progress. These tasks are usually related to reconciliations, repetitive journal entries, information consolidation, internal validations and close calendar tracking. By automating them, the finance team reduces manual work, gains traceability and can close with more reliable data in less time.

Accounting and bank reconciliations

Reconciliations are often one of the tasks that delay the close the most, especially when the team has to manually compare bank movements, accounting balances, invoices, collections and payments. Automating this process makes it possible to cross-check data faster, detect differences and reserve human review only for cases that truly require analysis.

Recurring journal entries, provisions and adjustments

Many closes include entries that repeat every month, predictable provisions, depreciation, reclassifications or periodic adjustments. When these tasks are performed manually, errors and dependence on specific people increase. Automation makes it possible to apply consistent rules, reduce omissions and ensure that entries are recorded using the same criteria in each period.

Financial consolidation and reporting

In companies with several entities, cost centres, currencies or business units, consolidating information can become a bottleneck. Automating consolidation and reporting helps reduce preparation times, eliminate duplicated versions and generate more reliable reports for management, audit or planning.

Validations, approvals and close calendar

The financial close does not depend only on data, it also depends on coordination. Automating validations, approvals and the close calendar makes it possible to know which tasks are pending, who is responsible for each one and where the blockers are. This improves traceability, reduces unnecessary emails and turns the close into a more organised and predictable process.

How to move from a manual close to a faster financial close

Moving from a manual close to a faster financial close is not just about adding a tool, but about organising the process from end to end. First, data must be centralised, then clear rules must be defined, the systems that feed the close must be integrated and, finally, the tasks that continue to cause delays must be measured. Only then does automation deliver real results instead of becoming another layer of complexity.

Centralise financial information

The first step is to prevent information from being spread across spreadsheets, emails, bank statements, ERP, CRM and internal files. When financial data is centralised, the team stops wasting time looking for versions, copying figures or manually checking whether the information matches.

A centralised data source makes it possible to work with updated balances, movements, invoices, collections, payments and adjustments, reducing errors and making it easier for all owners to consult the same information during the close.

Standardise rules, owners and deadlines

A fast close needs clear rules. This means defining which criteria apply to reconciliations, provisions, adjustments, approvals and validations, as well as assigning specific owners to each task.

When every activity has an owner, a deadline and review criteria, the close no longer depends on improvisation or undocumented knowledge. Standardisation makes the process repeatable, auditable and less vulnerable to bottlenecks, even if people in the team change.

Integrate ERP, reporting and planning

The financial close becomes more agile when the ERP, reporting tools and planning systems work together. If actual data is automatically integrated with reports, budgets and forecasts, manual workloads are reduced and teams avoid redoing analyses every time a figure is updated.

This integration means that the close is not only the end of the accounting period, but also the starting point for analysing deviations, updating forecasts and making decisions based on reliable data.

Measure times, errors and blocking tasks

To improve the close, it must be measured. It is important to identify how long each task takes, where most errors occur, which approvals are delayed and which processes generate the most rework. Without this data, it is difficult to know whether automation is solving the right problem.

Measuring the process makes it possible to prioritise improvements, adjust owners, eliminate unnecessary steps and check whether the close is really becoming faster and more reliable with each period. This way, improvement is no longer based on perceptions and starts relying on clear indicators of efficiency, quality and control.

Benefits of automating the financial close

Automating the financial close makes it possible to move from a slow, manual process dependent on constant reviews to a more agile, controlled and reliable model. The main improvement is not only closing earlier, but reducing errors, gaining traceability and freeing the finance team from repetitive tasks so they can spend more time on analysis and decision-making.

Main benefits:

• Faster financial close, by reducing manual reconciliations, data searches and repetitive tasks.
• Fewer errors and less rework, thanks to automatic rules, prior validations and less dependence on spreadsheets.
• Greater process traceability, with clear records of who reviews, approves or modifies each piece of data.
• More confidence in financial information, because data is centralised, updated and validated.
• Better team coordination, with visible owners, deadlines and task statuses.
• More agile reporting for management, with reports available earlier and with less manual effort.
• Greater analysis capacity, by freeing up time to review deviations, margins, forecasts and scenarios.
• Better audit readiness, thanks to more organised evidence, controls and close documentation.

When it is time to modernise the financial close

The time to modernise the financial close comes when the process starts to depend too much on manual effort and not enough on a reliable system. If every close requires reviewing spreadsheets, chasing approvals, correcting repeated errors or waiting for different teams to send information, the problem is no longer just operational: it affects data quality and the ability to make decisions on time.

It is also worth considering when the close takes longer and longer as the company grows. More entities, more accounts, more banks, more cost centres or a higher volume of operations make a manual model unsustainable. What could once be solved with internal control and extra effort ends up creating delays, team fatigue and slow reporting.

Another clear sign is a lack of confidence in the figures. If relevant adjustments, differences or reclassifications continue to appear after the close, it means the process needs more traceability, automation and control. Modernising the financial close helps reduce that uncertainty, improve process visibility and turn the close into a source of useful information, not a last-minute race.

La entrada How to accelerate the financial close when processes are still manual se publicó primero en Acevedo.

What is an AI agent?

An AI agent is an artificial intelligence system designed to achieve objectives autonomously, not just to generate responses. Unlike more passive AI solutions, an agent perceives its environment, reasons, plans and executes actions, typically interacting with data, tools and other systems without requiring a person to supervise every step.

In practice, an AI agent does not simply “say smart things”, but makes decisions and acts: it queries databases, calls APIs, executes workflows, evaluates results and adjusts its behaviour based on what happens. This is why we talk about action-oriented AI, not just content generation.

How is it different from traditional AI?

Traditional AI usually works in a reactive and limited way: it receives an input, applies a predefined model or set of rules and returns an output. It is highly effective for specific tasks (classification, prediction, recommendation), but it lacks real autonomy and the ability to coordinate complex, multi-step tasks.

An AI agent goes one step further because it:

• Works with goals, not just isolated instructions
• Plans how to achieve those goals by breaking them into steps
• Decides which actions to execute and in what order
• Learns from the outcome of its actions and improves over time

In short, while traditional AI responds, an AI agent acts. This makes it a key component for advanced business process automation and multi-step workflows.

Differences between a chatbot and an AI agent

Although they are often confused, a chatbot and an AI agent are not the same.

A chatbot is mainly designed to hold conversations. It answers questions, guides users and, in some cases, executes simple and very limited actions. Its behaviour is usually reactive: it waits for the user to input something before responding.

An AI agent, by contrast:

• Does not always depend on a conversation to act
• Can operate in the background, without a visible interface
• Executes real actions in systems (CRM, ERP, databases, internal tools)
• Makes autonomous decisions, even initiating tasks on its own

Put simply:

• The chatbot talks
• The AI agent thinks, decides and acts

That is why, while a chatbot can resolve questions or support users, an AI agent can manage entire processes, coordinate systems and automate operations end to end.

How do artificial intelligence agents work?

AI agents operate as goal-oriented cyclical systems. They do not follow a single linear path, but a continuous process in which they perceive, decide, act and learn. This cycle allows them to operate autonomously and adapt to changing contexts, which is essential when working with real data and enterprise systems.

Environment perception and data collection

Every AI agent starts by collecting information from its environment. This information can come from multiple sources: user interactions, internal databases, corporate documents, sensors, system logs, external APIs or real-time events.

The key point is that the agent does not operate blindly. Its ability to correctly perceive context directly determines the quality of its decisions. The better and more up-to-date the data, the more reliable the agent’s behaviour.

Reasoning and decision-making with LLMs

Once data has been collected, the agent uses one or more large language models (LLMs) as its “brain” to interpret information, understand context and reason about what to do next.

At this stage, the agent:

• Analyses the current situation
• Evaluates different possible options
• Selects the most appropriate action according to its objectives and rules

This is where an agent differs from simple automation: it does not execute fixed steps, but dynamically decides based on the situation.

Task and goal planning

After making a decision, the agent moves into planning. This involves breaking down a complex goal into smaller, manageable tasks, defining priorities and establishing a logical execution order.

For example, if the goal is to resolve an incident, the agent may plan to:

• Review the customer’s history
• Consult internal documentation
• Test possible solutions
• Escalate the case if it cannot be resolved

This planning capability allows agents to manage multi-step workflows without constant human intervention.

Autonomous action execution

After planning, the agent executes the required actions. These may include:

• Calling APIs
• Updating records in a CRM or ERP
• Sending emails or notifications
• Generating reports or responses
• Triggering other systems or agents

Execution is not just about “doing”, but about doing so with control, respecting permissions, limits and defined policies. A well-designed agent knows what it can and cannot do.

Learning and continuous improvement

The process does not end with execution. AI agents include feedback mechanisms to evaluate whether the outcome was correct.

Based on this evaluation, the agent:

• Adjusts future decisions
• Improves plans and priorities
• Learns from both mistakes and successes

This learning can be automatic, human-supervised or a combination of both. Thanks to this continuous cycle, AI agents improve with use and become more effective over time, rather than becoming obsolete after initial deployment.

Key components of an AI agent

An AI agent is not a single model or technology, but a system composed of several layers working together to enable autonomy, control and scalability.

Language model and LLM routing

The language model (LLM) acts as the agent’s cognitive core. In real environments, different models are often used depending on the task.

LLM routing allows the agent to:

• Select different models for reasoning, summarisation or extraction
• Combine specialised LLMs to improve accuracy and cost efficiency
• Apply rules governing when and how each model is used

This makes the agent more efficient, flexible and reliable at scale.

Identity, objectives and instructions

Every AI agent requires a clear identity: who it is, what role it plays and why it exists. Along with this, the following are defined:

• Core objectives
• Operational instructions
• Action boundaries

These are strategic rules, not simple prompts. Well-defined objectives lead to coherent behaviour aligned with business goals.

Tools, APIs and integrations

AI agents deliver real value when they can act on real systems. This requires access to:

• Internal and external APIs
• CRMs, ERPs and corporate systems
• Search engines, databases and cloud services
• Code execution and automation tools

These integrations turn the agent into a process orchestrator.

Memory and knowledge management

AI agents can remember and reuse information through:

• Short-term memory for context
• Long-term memory for persistent knowledge

Many agents also use RAG (Retrieval-Augmented Generation) to access up-to-date documentation and data, ensuring consistency and accuracy.

Governance, security and human control

Autonomy without control is risky. AI agents must include:

• Permission and access management
• Action logging and auditing
• Limits on critical decisions
• Human-in-the-loop validation

These mechanisms ensure that the agent operates in a secure, ethical, and compliant manner, especially in business environments where the impact of an error can be significant.

Types of AI agents

Not all AI agents are the same. There are different types of agents, designed to solve problems with increasing levels of complexity, autonomy, and adaptability. Choosing the right type depends on the environment, the level of acceptable risk, and the objectives of the system.

Simple reactive and model-based agents

Simple reactive agents operate using direct rules such as “if X happens, do Y.” They have no memory or historical context, so they do not learn or plan. They are fast, predictable, and useful for very specific tasks, but limited in complex scenarios.

Model-based agents add an extra layer by maintaining an internal model of the environment. This allows them to make better decisions by considering the current state of the system, although they still do not learn in a deep way. They are commonly used in control systems, simulations, or partially observable environments.

Goal-oriented and utility-based agents

Goal-oriented agents do not just react; they act to achieve a specific goal. They evaluate different possible actions and choose the one that best helps them reach the defined objective. They are well suited for task planning and workflow management.

Utility-based agents go a step further: instead of simply achieving a goal, they aim to maximise a value or utility. They compare options based on expected benefits, costs, or risks. This approach is key in recommendation systems, optimisation, and strategic decision-making.

Learning agents and multi-agent systems

Learning agents can improve their behaviour over time through experience and feedback. They use techniques such as machine learning or reinforcement learning to adapt to changing environments. They are especially valuable when it is not possible to define all rules in advance.

Multi-agent systems are made up of several agents that collaborate or compete with each other to solve complex problems. Each agent can have a different role, and the system as a whole achieves objectives that would be unattainable for a single agent. They are used in process orchestration, logistics, advanced simulations, and distributed environments.

How to implement an AI agent step by step

Implementing an AI agent is not just “plugging in an LLM” and calling it a day. For it to work in a real environment (and not just as a polished demo), you need a well-defined use case, reliable data, well-integrated tools, and a system for control, testing, and monitoring. The safest way to start is with a measurable pilot and then scale your business with AI.

Step 1: Choose a pilot use case and define objectives

Start with a use case where the agent can deliver clear and fast value. The key is to define what “working” actually means: objectives, scope, boundaries and KPIs (for example, time saved, resolution rate, ticket reduction, response accuracy or cost per task). Poor pilots usually fail due to overambition: scopes that are too broad, too many dependencies or unclear metrics.

Step 2: Prepare data and knowledge (internal sources, RAG)

An agent is only as good as the information it can access. At this stage, you must decide which sources it will use: internal documentation, FAQs, policies, tickets, databases, ERP/CRM systems, and so on. With RAG, these sources are connected so the agent can respond and decide using up-to-date information. This is also the moment to clean duplicates, define a single source of truth and control access by roles.

Step 3: Define tools, integrations and permissions

The agent needs “hands”: APIs and tools to execute real actions. Define which systems it will interact with (ERP, CRM, ITSM, email, calendar, BI, etc.) and what permissions it will have. Best practices include the principle of least privilege, test environments, service-based credentials and human approval for critical actions. Without proper permission control, risk increases significantly.

Step 4: Design prompts, workflows and action boundaries

This is where the agent’s “behaviour” is built: instructions, tone, rules, output formats and, most importantly, limits. Define when the agent should request more information, when it should escalate to a human and which actions are prohibited. In enterprise agents, it is essential to design workflows (not just prompts) and to establish a HITL (human-in-the-loop) system for sensitive decisions.

Step 5: Test, evaluate and refine (tests and metrics)

Before going into production, you need tests that simulate real scenarios: normal, ambiguous and adversarial cases. Measure both quality and safety: accuracy, coverage, escalation rate, errors, response time and cost per interaction. It is common to iterate on prompts, RAG sources, rules and tools until the agent becomes stable and predictable.

Step 6: Deploy and monitor (logs, quality, costs)

In production, observability is critical. This includes logs of inputs, decisions, tool calls and outcomes. Add dashboards and alerts to detect degradation, hallucinations, integration failures, cost spikes or unexpected behaviour. An agent without monitoring quickly becomes a “black box” and, sooner or later, a problem.

Step 7: Iterate with continuous improvement and human control

An agent is not a “set and forget” system. It must evolve with new data, process changes, user feedback and model improvements. Define a review cycle that includes conversation analysis, knowledge updates, policy adjustments and risk assessment. Always keep a layer of human control for critical actions and a clear continuous improvement plan with well-defined priorities.

Frequently asked questions

La entrada What is an AI agent and what is it really used for? se publicó primero en Acevedo.

The best ERP systems on the market in 2026

Before comparing vendors, it is worth reviewing five key points:

• Company size
• Process complexity
• Need for customization
• Cloud or hybrid approach
• Budget and implementation

A commercial SME does not need the same thing as an industrial company or an international group. That is why, rather than focusing on which ERP systems are the best known, it is more useful to see which solution tends to be the best fit for each scenario.

1. Oracle NetSuite ERP

Oracle NetSuite ERP is one of the strongest options for companies that need a complete cloud solution without yet moving into heavier enterprise suites. NetSuite presents it as an all-in-one ERP powered by AI to automate core processes and provide real-time visibility into financial and operational performance. Oracle also states that NetSuite serves more than 43,000 customers.

It is usually a very good fit for growing companies that want to centralize finance, operations, inventory, orders, and reporting on a single platform. Because of its functional breadth and cloud maturity, it tends to rank very highly in any selection of the best ERP systems for businesses.

2. SAP Cloud ERP

SAP Cloud ERP, formerly known as SAP S/4HANA Cloud Public Edition, continues to be a clear reference point for large organizations or companies with complex processes. SAP defines it as a ready-to-run cloud ERP designed to connect business processes and transform the way companies operate.

It is an especially strong option for companies with high operational complexity, international presence, or advanced needs in finance, supply chain, and manufacturing. For large enterprises, it remains one of the most common names in any serious ERP comparison.

3. Microsoft Dynamics 365 Business Central

Business Central is one of the most widely used ERP systems among SMEs and mid-market companies. Microsoft defines it as a comprehensive business management solution for small and medium-sized businesses, with capabilities for finance, sales, and operations, and with Copilot included in its current plans.

It stands out particularly when a company already works with Microsoft 365, Power BI, or the wider Microsoft ecosystem and is looking for a reasonably agile implementation with a good user experience. For many SMEs, it is among the best options due to its balance between functionality and technological familiarity.

4. Odoo

Odoo has established itself as one of the most attractive alternatives for SMEs and mid-sized companies that value flexibility and a modular approach. The company defines it as an open-source platform for managing a business through multiple integrated apps within a single solution.

Its main appeal lies in the ability to grow module by module, adapt the scope, and maintain a fairly unified experience. That is why it frequently appears among ERP solutions for businesses that do not want to start with an overly heavy suite.

5. Sage Intacct

Sage Intacct has a strong focus on cloud financial management. Sage states that it is its AI-powered financial software for growing businesses, offering real-time visibility, more than 350 integrations, and use by more than 30,000 finance teams.

It is not always the first name people mention when they think of a general ERP, but it is one of the most interesting options when the real weight of the project lies in finance, consolidation, reporting, and automation of the finance function.

6. Acumatica

Acumatica Cloud ERP is presented as a fully integrated system for finance, manufacturing, construction, distribution, professional services, and retail. The company defines it as a modern, adaptable cloud ERP designed to improve efficiency and scale with confidence.

It is a very interesting option for mid-sized businesses looking for a cloud ERP with industry-oriented capabilities, strong adaptability, and a less rigid model than some more traditional suites.

7. Infor CloudSuite

Infor places a strong emphasis on the vertical approach. Its CloudSuite offering is presented as a family of cloud ERP solutions built on industry best practices and powered by an intelligent AI-driven platform.

It usually makes more sense when a company needs deep industry-specific functionality, especially in manufacturing, distribution, or other product-centric environments. That is where it tends to differentiate itself most clearly from more horizontal solutions.

8. Epicor Kinetic

Epicor Kinetic is clearly geared toward manufacturers. Epicor defines it as a global cloud ERP designed for and with manufacturers, with real-time business intelligence and integrated collaboration tools.

If your company’s operations are closely tied to plant management, production, materials, and industrial processes, Epicor is usually an option worth considering within the manufacturing ERP market.

How to choose the best ERP for your company

The right question is not only which is the best ERP on the market, but which one fits your business. For a growing company that needs global visibility and a mature cloud stack, NetSuite is often a very natural option. For a large organization with high complexity, SAP or Oracle tend to carry more weight. For SMEs and mid-market companies, Business Central, Odoo, or Sage Intacct may be a better fit depending on the case.

Before making a decision, it is important to review how well the solution integrates with your processes, its real functional scope, ease of implementation, scalability, partner ecosystem, and total cost. That is usually where the difference lies between choosing one of the best ERP systems and ending up with a tool that is either too limited or too big for your needs.

La entrada Best ERP Systems on the Market in 2026 for Businesses se publicó primero en Acevedo.

What application modernization is

Application modernization is the process of improving existing applications so they can adapt to current business and technology needs. In some cases, this means moving them to the cloud. In others, it involves redesigning parts of the architecture, modernizing integrations, automating deployments, or improving the environment in which the application runs.

This also includes legacy application modernization, meaning the evolution of legacy systems that are still important to the business but make change, scaling, or integration with new services more difficult.

Many legacy applications are still running, but that does not mean they are ready for today’s business pace. They often create problems such as slow changes, complex integrations, higher maintenance costs, difficulty scaling, and dependency on outdated technologies. Modernization aims precisely to reduce that friction and allow the application to continue delivering value without becoming a bottleneck.

The role of integrations in modernization

Integrations are a key part of the process. An application may be reasonably up to date, but if it still depends on rigid connections, manual processes, or point-to-point integrations, the end result will still be limited.

That is why modernization also means reviewing how systems connect with each other. This affects APIs, ERPs and CRMs, SaaS tools, databases, and internal and external processes. In many companies, integration is one of the areas where the difference between a legacy architecture and an architecture prepared for growth becomes most visible.

Key layers of application modernization

Application modernization can be approached from several layers, and not all of them address the same problem. In some cases, the focus is on improving how software is built; in others, on organizing how it is planned, deployed, and maintained over time; and in others, on updating the environment where the application runs and scales. That is why it is useful to distinguish between application development modernization, application lifecycle modernization, and application runtime modernization.

Application development modernization

Application development modernization focuses on how software is built. This includes practices such as automation, DevOps, continuous integration, containers, or managed services.

The goal is to develop faster, with fewer errors, and on a stronger foundation for future evolution.

Application lifecycle modernization

Application lifecycle modernization affects the entire journey of the application: assessment, planning, deployment, operation, and continuous improvement.

This means modernization is not a one-time action, but an ongoing process. The application is not only updated; it is also prepared to keep evolving with less friction.

Application runtime modernization

Application runtime modernization focuses on the environment where the application lives and scales. This includes decisions such as moving workloads to containers, using Kubernetes, taking advantage of managed platforms, or reducing dependence on rigid infrastructure.

This is an important layer because many limitations are not only in the code, but in how the application runs in production.

Common application modernization strategies

Once the part of the application that needs to be modernized has been defined, the next step is to choose the right approach. Moving an application with minimal changes is not the same as adapting its technology base to reduce operational burden, modifying parts of the code to gain flexibility, or evolving toward containers and Kubernetes to improve deployment and runtime. That is why strategies such as rehost, replatform, refactor, or evolving to containers and Kubernetes respond to different needs.

Rehost

This involves moving the application with minimal changes. It is usually useful for getting off legacy infrastructure quickly, although it does not solve architectural issues on its own.

Replatform

This means adapting part of the technology base to reduce operational burden and improve performance without rebuilding the whole application.

Refactor

This involves modifying parts of the code or architecture to gain flexibility, scalability, and greater ability to evolve.

Evolving to containers and Kubernetes

When the goal is greater portability, better runtime management, and more consistent deployments, containers and Kubernetes are often a common choice.

Modernization approaches and business benefits

Not every modernization process pursues the same goal. Some companies prioritize leaving legacy infrastructure behind as quickly as possible. Others aim to reduce operational complexity, improve architecture, or gain flexibility for future changes.

A well-planned modernization usually brings greater agility for launching changes, better scalability, less dependence on rigid environments, better integration with new systems, less operational friction, and more ability to evolve without rebuilding everything.

The real value lies not only in the technology itself, but in the ability to respond faster to new business needs.

When it makes sense to start an application modernization process

There are fairly clear signs that a company should consider modernization:

• Time to market is too slow
• A simple integration becomes complex
• Maintenance costs more than evolution
• The current architecture limits growth
• The team spends more time fixing than improving

In these cases, modernization stops being an optional improvement and becomes a real necessity.

Preguntas frecuentes sobre modernización de aplicaciones 

La entrada Application and Integration Modernization: What It Is and Why It Matters se publicó primero en Acevedo.

Key Differences Between Oracle Autonomous Database and Snowflake

Oracle Autonomous Database is positioned as a fully autonomous database, with elastic scaling and no need for traditional database administration. Snowflake, by contrast, structures its offering around compute warehouses that execute SQL queries and other workloads, clearly separating compute and storage. In other words, Oracle focuses on automating the database, while Snowflake focuses on decoupling compute for different workloads.

Platform Model

Oracle describes Autonomous AI Database as a “fully autonomous” database that scales elastically and requires no database administration. Snowflake defines a virtual warehouse as a cluster of compute resources that provides CPU, memory, and temporary storage to run queries and other operations.

In Oracle Autonomous Database, patching and updates are automated by Oracle, and daily administration is greatly reduced compared to traditional DBA tasks. Optimization is focused on automating the database lifecycle, so the operational focus remains on the database itself.

In Snowflake, although it is also a managed service, daily operations are more centered on governing warehouses, adjusting their size, configuring automations, suspensions and resumptions, and controlling compute consumption and performance.

Management and Administration

Oracle states that Autonomous AI Database autonomously manages aspects of the database lifecycle, from placement to backup and updates. Snowflake documents warehouse management as a central part of daily operations, including sizing, automation, and warehouse administration tasks.

Scaling and Concurrency

Oracle Autonomous Database provides elastic scaling with auto scaling, managing concurrency within the autonomous service itself. When demand spikes occur, it can expand CPU capacity as needed. In Snowflake, scaling is done through warehouses, which provides great flexibility by separating workloads and assigning specific resources to each one. In addition, workload isolation is a very visible part of its value proposition.

Workloads and Use Cases

Oracle Autonomous Database is designed for transactional workloads, analytics, lakehouse, JSON, and application development, as well as low-code services with APEX. Snowflake also covers analytics scenarios and allows working with SQL and code through Snowpark, but it is not as focused on transactional workloads or low-code development as a central part of its value proposition.

Pricing and Purchasing Model

In Oracle Autonomous Database, the main compute unit is the ECPU, and storage is billed separately. There are serverless, dedicated, and BYOL options across different offerings. In Snowflake, the model is consumption-based, with compute measured in credits and storage billed separately per TB per month.

From a cost perspective, Oracle may be especially attractive for organizations that already work with Oracle technology and want to consolidate services within its ecosystem. Snowflake, meanwhile, offers a very flexible model for managing spend through independent warehouses.

When Oracle Autonomous Database or Snowflake Is the Better Choice

Oracle Autonomous Database makes more sense when the priority is to have a highly automated Oracle database, with less administrative burden and support for multiple types of workloads within the Oracle ecosystem. This is especially relevant when the company is not only looking for an analytics layer, but also needs to support transactional workloads, low-code development with APEX, JSON-based applications, or a more unified approach to data and applications.

Snowflake can be a very good fit in scenarios where the main focus is on separating analytical workloads and decoupled compute by teams or use cases. But for an Oracle-focused page, the most useful angle is not to present both products as equivalent, but to explain that Oracle Autonomous Database stands out when the main challenge is reducing operational complexity in the database and taking advantage of a more automated and versatile Oracle platform.

La entrada Oracle Autonomous Database vs. Snowflake: Which One to Choose se publicó primero en Acevedo.