We advise and build at the intersection of AI, engineering governance, and regulated-domain assurance — turning capability into a durable, governable advantage.
The practice is grounded in two decades of operating leadership across every layer of the modern technology stack — power electronics and embedded systems, IoT and edge platforms, enterprise cloud and SaaS, enterprise and platform architecture, AI strategy and governance, and the standards and verification discipline that connects them. Depth in one layer is common; fluency across all of them, and the judgment to connect them, is not.
We advise on engineering-organization design and operating models; AI strategy and governance — turning NIST AI RMF and ISO/IEC 42001-class frameworks into real controls, not policy decks; platform and systems architecture; and technology M&A and diligence.
We design and build production AI — multi-agent workflows, skills, and systems — for real operating use, each with a verification layer at its core. Our engineering rigor runs end to end: L100–L300 requirements discipline, test- and behavior-driven development, domain-driven design, and model validation.
We don't only advise on AI; we build it — and we build it to hold up where the cost of being wrong is real.
Non-practice strategy and policy advisory for technology organizations and standards bodies — distinct from, and parallel to, the affiliated law practice. We help operationalize AI governance as a control framework rather than a policy document.
It rests on deep standards and verification work — engineering verification and validation (NASA-STD-7009B / IEEE 1012 class), simulation credibility, and a companion AI-maturity line — pursued research-first, alongside IP strategy and inventor-defensibility.
In regulated, liability-heavy work, the hard problem with AI isn't capability — it's trust. A system that's right most of the time is unusable when a single unsupported citation or missed authority carries real consequence. [Un]labs is building a next-generation platform for legal case- and citation-management with assurance engineered into its core: the work isn't just produced — it's evidenced, and it stays under human control. The differentiator isn't generation; it's verification — provenance, source-anchoring, and gates built to the same independent-validation discipline that governs safety-critical systems. We're proving it first where the bar is highest — accuracy-critical legal work — because that discipline transfers directly to the other regulated domains (compliance, healthcare, finance) that share the same shape: confidential, liability-bound, and unforgiving of error.