What we do

Software modernization that enables AI.

Our modernization service helps organizations with legacy platforms or applications by determining the best way forward, modernizing the systems, and enabling AI in both process and product.

How modernization and AI relate

AI produces reliable results when the systems and data underneath it are in order. Modernization and AI implementations can each stand on their own, and they strengthen each other when combined. The assessment determines where an engagement starts.

Every automated step follows the same principle: prepared by the machine, checked by a person. Rules and criteria live in adaptable knowledge bases, so the software moves with changing regulation instead of hard-coding today's rules.

Every route starts the same way

Assessment

Assessment

An analysis of the existing platform, the data flows, and the processes around them. No route gets chosen before the system is understood, because legacy platforms hold years of business logic that exists for a reason.

The findings determine what gets rebuilt, what gets modernized, and what stays. Sometimes the advice is to change less than expected, and that advice is part of the service.

  • A documented picture of the platform, the data, and the risks
  • The route: rebuild, modernize in parts, or keep
  • Phases and costs, known upfront

Modernization

The platform gets brought up to standard while daily operations continue. The work follows the route from the assessment, whether that means a complete rebuild or targeted changes.

After modernization, feature development and maintenance speed up instead of slowing down each year. The backlog starts moving, and AI-assisted development works properly on a clean, documented codebase.

  • A modern, documented system the internal team can work with
  • Integrations that remove double entry between systems
  • Feature development that gets faster, and a next change that gets cheaper

AI in process and product

On a foundation that can carry it, AI takes over repetitive work: document handling, data entry, checks. In the process, that means fewer hours on administration. In the product, it means software that reads, structures, and prepares work on its own.

Staff keep the final say on every outcome. The models run on European hosting, in compliance with the GDPR and the AI Act.

  • Automation that demonstrably saves hours in the daily work
  • Human control over every automated decision
  • Knowledge bases the organization can adapt as rules change

The tracks run on their own or in sequence. When combined, modernization comes first, and the AI lands on a foundation that can carry it.

AI in the work itself

The same principle applies to how Eli5 builds. AI assists throughout the assessment and the development work, and an engineer reviews everything that ships.

In the assessment:

AI helps read existing codebases and reconstruct thin documentation, so years of accumulated business logic surface in weeks instead of months.

In development:

AI-assisted engineering speeds up building and testing, and it performs best on a clean, documented codebase. Modernization produces exactly that, so the gains compound over time.

The rule:

Prepared by the machine, checked by a person. The rule Eli5 applies to client work applies to its own engineers as well.

One case per dimension

The service, seen in practice

Modernization

Total Energies

Contract and quote processing rebuilt into one automated flow, connected to the CRM, EDSN, and the grid operator.

AI in process

Headfirst

Candidate interviews transcribed, summarized, and entered into the recruitment system, with recruiters making the final assessment.

AI in product

Zenday

An accounting platform where AI monitors and matches transactions, and accountants make the final call.

All cases →

The engineers who scope the work also build it. Compliant with European rules such as the GDPR and the AI Act.

Common questions

Straight answers to the questions that come up in most first conversations.

Does modernization always mean a complete rebuild?

No. The assessment determines the route, and the outcome ranges from a complete rebuild to targeted changes. Sometimes the advice is to change less than expected, and that advice is part of the service.

Does the daily operation stop during modernization?

No. The platform gets brought up to standard while daily operations continue. Continuity is a requirement of the work, planned for from the assessment onward.

Can AI be implemented without modernizing first?

When the platform and the data are sound, yes. The assessment establishes whether that is the case. When the foundation cannot carry reliable AI yet, that finding comes first, with the route to fix it.

Does Eli5 use AI during the work itself?

Yes. AI helps read existing codebases during the assessment and assists in building and testing during development. An engineer reviews everything that ships, following the same rule Eli5 applies to client work: prepared by the machine, checked by a person.

Which AI models does Eli5 work with?

Models from OpenAI via Microsoft Azure, Anthropic, and Google, chosen per engagement. The models run on European hosting, in compliance with the GDPR and the AI Act.

What does human in the loop mean in practice?

AI does the preparatory work, such as reading documents, entering data, and running checks, and staff make the final call. Rules and criteria live in adaptable knowledge bases, so the software moves with changing regulation.

Who does the work?

A team of around twenty engineers with fifteen years of experience. The engineers who scope the work also build it, and the direct contact is a partner rather than an account layer.

How does an engagement start?

With an assessment of the existing platform, the data, and the processes around it. The first conversation about it is free of charge and without obligation.

Start with an assessment

Talk to a humanTalk to a humanSubmit an RFP or RFISubmit an RFP or RFI
Floris Schoenmakers · Partner

The first conversation, what it covers

Forty-five minutes on the organization's situation rather than a pitch.

  • The platform, its age, and who built it
  • Where the daily work gets stuck
  • Whether an assessment makes sense, and what it would look at