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
What we do
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.
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.
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.
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.
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.
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.
The same principle applies to how Eli5 builds. AI assists throughout the assessment and the development work, and an engineer reviews everything that ships.
AI helps read existing codebases and reconstruct thin documentation, so years of accumulated business logic surface in weeks instead of months.
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.
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
Total Energies
Contract and quote processing rebuilt into one automated flow, connected to the CRM, EDSN, and the grid operator.
Headfirst
Candidate interviews transcribed, summarized, and entered into the recruitment system, with recruiters making the final assessment.
Zenday
An accounting platform where AI monitors and matches transactions, and accountants make the final call.
The engineers who scope the work also build it. Compliant with European rules such as the GDPR and the AI Act.
Straight answers to the questions that come up in most first conversations.
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.
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.
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.
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.
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.
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.
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.
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.
Forty-five minutes on the organization's situation rather than a pitch.