Spec-driven development, agent-accelerated.
Fingrid itself is built with the discipline we sell: a formal specification suite covering every module, AI agent pipelines that build against those specs, and provenance on every AI-assisted change. It's why a lean team ships an enterprise platform — and why what ships matches what's specified.
How spec-driven, agent-accelerated engineering works
Specification-first
Every module begins as a layered specification — domain rules, data model, workflows, screens — before code exists.
Agent pipelines
AI agents build against the specs: parameterised generation for lender integrations, document types and configuration deltas.
Spec-drift detection
Automated loops compare the running system against its specification and flag divergence — the spec stays true, not decorative.
AI provenance
Every AI-assisted change is labelled: which agent, which spec, which human reviewed. Nothing merges anonymously.
Gate discipline
Formal review gates and code ownership on every change — AI raises throughput, not risk.
Compounding skills
Engineering knowledge is encoded as reusable skills the agents apply — each integration makes the next one faster.
Why this matters to a buyer
Engineering method sounds internal until you're the one depending on it:
- Delta development at configuration speed — lender-specific changes build against specs, not from scratch
- New integrations follow proven, parameterised pipelines rather than heroic one-off projects
- Auditability extends to the code itself: what the system does is written down, and drift is detected, not discovered
- A platform this broad stays coherent because the specification, not tribal memory, is the source of truth
Judge the method by its output.
Ask us how a lender-specific delta goes from requirement to production.