Designed for real engineering adoption
Deterministic AI for safety- and compliance-critical work
We design AI that behaves like an engineering system—not a creative chatbot. Outputs are bounded by governed sources, explicit citations, and version-aware references to reduce hallucination risk and improve trust.
Built by engineers, for engineers
We understand engineering constraints in practice—safety, quality, schedule pressure, change control, audit requirements, and the high cost of errors. Our solutions are designed for real operational adoption, not demos.
Beyond indexing: engineering understanding and workflow integration
Many RAG solutions stop at document ingestion and retrieval. We design systems that understand engineering manuals and operational context—so outputs are actionable and aligned to the actual steps engineers must execute.
Governed, traceable references for defensible outcomes
Our AI outputs are anchored to authoritative sources with clear citations, version awareness, and traceability. This reduces hallucination risk and improves confidence in regulated or safety-critical environments.
Integrated approval and accountability
Engineering decisions require control. We embed review and sign-off workflows (approval, exception handling, escalation paths) so the human remains accountable while AI accelerates drafting, comparison, evidence gathering, and decision preparation.
Security-by-design across cloud, data, and AI
Because cybersecurity is a core practice, we integrate identity, access, data leakage controls, secrets handling, logging, and governance into every solution—especially for LLM and RAG deployments.
Fast validation with production discipline
We deliver rapid prototypes in two weeks using customer datasets, then harden and scale to production using modern DevOps: testing, CI/CD, monitoring, and operational runbooks.