AI systems: build and run
Not advice, built. AI agents, automation, and production platforms designed, built, and run to a standard that survives a regulator and a codebase, not a prototype that dies after the demo.
Who it is for
Institutions that need working AI in production, with the governance and verification that let them rely on it.
What you get
- AI agents and multi-agent systems that act reliably within set boundaries
- Workflow automation across real operations
- Retrieval and knowledge systems grounded in your data
- Evaluation and quality-assessment harnesses so you can trust the output
- Production deployment, monitoring, and the governance around it
How it works
- Fix the right problem before building
- Build to production standard, not slideware
- Adversarially verify before anything ships
- Deploy, monitor, and run
Questions
Do you build, or just advise?
I build. Systems delivered to production standard, then verified before they go live. Advice without a working system is where most AI projects fail.
Can you work in a regulated or on-premise environment?
Yes. The build is designed from the start to satisfy the governance, data-residency, and verification requirements of regulated and sovereign settings.
Discuss this work
Related: Governing AI that acts · The Crucible verification method · AI governance & compliance · All services