Augment
Add AI where the application stands.
Summaries, extraction, validation, search or drafting added through one OpenAI-compatible API. No rewrite: the application calls a governed endpoint.
Modernise — Brownfield AI modernisation
Bring AI to the systems you already run.
Much of an enterprise’s value sits in applications that are ten or twenty years old: an order system, a claims tool, a service database. Replacing them to get AI is rarely the answer. Onega assesses your estate, adds AI where the application stands, turns legacy functions into safe tools for agents, and migrates step by step only where the numbers say it pays.
01 — Four patterns
One decision per application.
Wrap
Turn legacy functions into safe tools.
Legacy functions and data exposed as well-defined, permissioned tools, so agents can use the system without screen scraping or direct database access.
Migrate
Move in slices, not in one leap.
One capability at a time behind a stable interface, with AI-assisted code analysis and tests written before anything moves. Old and new run side by side until the new one is proven.
Retire
Replace the role, keep the record.
Where a workflow is better served by an agent or an Onega product, the application’s role is replaced and its data archived under your retention rules.
02 — AI-assisted engineering
AI speeds up the work. Engineers stay responsible for it.
Legacy code is where AI-assisted engineering saves the most time and where it can do the most damage. Every generated change is reviewed, tested against the characterisation suite and merged by a person.
- Code comprehension: models help map large, thinly documented codebases, their dependencies, business rules and data flows.
- Characterisation tests: tests that capture what the system does today, written before any change.
- Translation and refactoring: models draft conversions between languages and frameworks; engineers review every change.
- Documentation: the business rules found in the code are written down for the people who own them.
- Containment: source code stays in your environment, and models used on it run locally or through a provider route you have approved.
03 — How it runs
Assess the estate, prove one slice, then scale.
- 01
Modernisation Assessment · 3–4 weeks
Application inventory, code and data analysis, a pattern per application, risks, a sequenced roadmap and a fixed-price proposal for the first slice.
- 02
First slice · 6–8 weeks
One capability augmented, wrapped or migrated in your environment, with characterisation tests and a rollback path.
- 03
Parallel run
Old and new side by side on real work until the new path matches or beats the baseline.
- 04
Roadmap delivery
Further slices through a Forward Residency, each reusing what the previous slice built.
04 — Starting points
Where modernisation usually begins.
- Order, claims, service and case-management applications with a database behind them
- Client-server and early web applications on .NET Framework, Java EE, Delphi or Visual Basic
- Mainframe-adjacent systems reached through files, queues or APIs
- Document-heavy processes held together by shared drives and email
- ERP and CRM customisations that block the next upgrade
- Integration layers that agents need to reach safely
05 — FAQ
Questions application owners ask.
Do we have to rewrite an application to use AI?
Usually not. Augmenting or wrapping an application gives it AI capabilities through a governed API while it keeps running as it does today. We recommend migration only where the assessment shows that it pays.
Can AI safely work on our source code?
With conditions: the code stays in your environment, models run locally or through a provider route you approve, every generated change is reviewed and tested by an engineer, and nothing is merged without a person.
What happens to the old system during a migration?
It keeps running. Each slice runs beside the old path until it is proven on real work, and every slice has a rollback path.