Private AI Software Engineering
Generative AI systems that enter business processes and stay there. Architectures, gates and verifications to bring them into production without turning every project into a fragile experiment.
AI accelerates.Systems thinking governs.Verification makes it deliverable.
The principle
Data, prompts, outputs, controls, formats, gates, traceability and explicit acceptance criteria. We don't promise to make the LLM deterministic — that would be a technical lie. We promise to make the process around it verifiable and repeatable.
Three concrete examples
Not philosophy. Systems that keep working after the demo is accepted and signed.
1 · Contract knowledge base
A user asks about a clause. The system answers citing source document, paragraph used, model invoked, prompt applied and operational confidence level. The demo gives the answer. The system gives the answer together with the evidence that makes it acceptable inside the company.
2 · Document workflow
A document enters. The pipeline classifies it, extracts data, flags ambiguity, produces a controlled-format output and blocks unverifiable cases, routing them to a human operator. The demo processes everything and fails. The system processes what it can reliably — and flags the rest instead of confabulating.
3 · AI-assisted software delivery
A code change isn't just generated by AI. It's analyzed, tested, documented, checked against project constraints and accepted only if it passes explicit criteria. The demo produces diffs. The system produces diffs that can enter main.
Two paths
Same technical stack, two different starting points. We begin where you are.
A · Guided start
Installation of private AI environments, conversational interfaces, document knowledge bases, automation and maintenance. Configured, integrated with corporate identity, monitored and documented. Turnkey.
B · Production systems
Method assessment, redesign of existing AI processes, acceptance gates, verifiable pipelines, controlled output formats, human-in-the-loop integration, traceability. For organizations that ran the demo, hit the limits, and need to go to production.
A short technical assessment determines whether we can help, on what timeline, and with what concrete deliverables.
