Why rebuild, not patch
Putting in place the AI foundation
Most businesses aren't running one system — they're running years of patches bolted onto whatever came before. Rebuilding deals with that. But the real point is what it enables: a platform ready for AI to work continuously, at a fraction of the cost.
The rebuild itself follows a set process, not guesswork: we ingest the legacy code, data, and history with no documentation required, AI specifies the architecture, quality checks, and outcome contract from what we actually found, and connected AI systems build it under human review — five quality checks on everything shipped, 73% AI-written, 100% human-approved. That's what sets the new foundation, not just patches it.
Re-platformed for AI
Work continuously, at a fraction of the cost
The system doesn't stop working when we leave. Every change is checked and logged automatically, and the documentation updates itself from how the system actually behaves — not how it was designed to. Maintenance, enhancements, and regulatory pace stop compounding and become continuous, in the background, at a fraction of the cost.
Once it's live, that same discipline keeps going: AI keeps triaging issues, quality checks keep running, and the audit record keeps growing in your own repo — so everything stays current without ever needing to re-engage us.
Built for the full SDLC
From legacy system to production — EffektAI spans every phase.
It's the same idea the big consultancies use at enterprise scale, built for businesses of every size at a fraction of the price — and with no lock-in.
Ingest
We read the legacy code, data, and history. No documentation required.
Specify
AI generates the architecture, quality checks, and outcome contract from what we found — not from a template.
Build
Connected AI systems write the code under human review. Five quality checks on everything. 73% AI-written, 100% human-approved.
Ship
The switchover is rehearsed on a copy of the live system first. Rollback plans are agreed upfront. Your team runs the actual switch.
Operate
AI keeps triaging issues, quality checks keep running, and the record keeps growing in your repo — kept current without re-engaging us.
What AI-first means in practice
AI does the work AI is good at. Humans own the work that requires judgement.
What AI handles
- Code authoring under senior direction
- Rebuilding tests from how the system actually runs
- Data migration — written, run, corrected, re-run
- Quality checks and connecting systems together
- Reading legacy systems the documentation never captured
- Triaging alerts and resolving known issues
What humans own
- Architecture decisions — every load-bearing call
- Security sign-off before anything ships
- Anything that touches money or a record of truth
- Contract terms and the metrics that define success
- The moment something needs a human judgement call
- A named accountable person on every automated decision
That division is what makes the foundation trustworthy at enterprise and government scale — speed where AI is faster, judgement where it isn't.
Common questions
Frequently asked questions.
How long does a rebuild take?
It depends on the system, but the process runs through five phases — Ingest, Specify, Build, Ship, Operate — with Ingest and Specify typically taking one to two weeks before a fixed-fee proposal is issued. Full rebuild timelines are scoped project by project; see our published pricing models for typical ranges.
Do we need existing documentation for you to work on our system?
No. EffektAI is built to ingest legacy code, data, and history with no documentation required — it reads what the system actually does, not what a document says it should do, and surfaces undocumented fields and hidden dependencies before a line of the rebuild is written.
How much of the code is actually written by AI, versus a human?
On a well-run engagement, AI authors roughly 73% of the code. Every line goes through five quality checks and 100% human review before it ships — AI does the authoring, humans own architecture decisions, security sign-off, and anything that touches money or a system of record.
What happens to our system once the engagement ends?
It keeps running under the same discipline it was built with. Every change continues to be checked and logged automatically, documentation updates itself from how the system actually behaves, and AI keeps triaging issues and running quality checks in the background — so maintenance and enhancements continue without needing to re-engage us.
How is this different from just hiring developers who use AI coding tools?
Individual developers using AI tools still rely on their own judgement for architecture, quality gates, and documentation — which varies person to person. EffektAI standardises all of that into one platform: the same ingestion process, the same five quality checks, and the same audit trail on every engagement, regardless of who is staffed on it.
Can you migrate off a legacy platform without downtime?
Yes — the switchover is rehearsed on a copy of the live system first, rollback plans are agreed upfront, and your team runs the actual cut-over. We've completed migrations from systems like IBM AS/400 to cloud with no rollback required.
One foundation. Ongoing advantage.
See what the AI foundation could do for your business.
Tell us what you're running now. We'll show you what putting the right foundation in place — once — unlocks: faster maintenance, faster enhancements, and regulatory pace, all at a fraction of the cost.