Two disciplines, one standard of rigor.
We work with enterprises in regulated, high-stakes environments — advising on the systems they trust, and building the products they ship.
AI Consulting & Governance
AI you can put in front of a regulator. We map strict controls and regulatory adherence directly into your AI pipelines — so model safety, data residency, and auditability are properties of the architecture, not afterthoughts.
What's included
- —AI strategy & architecture review
- —SOC 2 control mapping for ML/LLM pipelines
- —Data residency & sovereignty design
- —Model safety, evaluation & red-teaming
- —Vendor & sub-processor risk assessment
- —Audit-ready evidence automation
How we engage
- 01AssessA structured audit of your pipelines, data flows, and exposure.
- 02MapTranslate trust criteria into concrete, enforceable controls.
- 03BuildImplement guardrails and automated evidence into the system.
- 04SustainHand over controls your team can run without a fire drill.
Mapping SOC 2 Controls Into AI Pipelines
How to translate SOC 2 trust criteria into concrete controls for LLM and ML systems — without grinding delivery to a halt.
Governance · 7 min readData Residency for Enterprise AI: A Practical Playbook
Where your data lives — and where your model quietly sends it — is a board-level question. A pragmatic approach to residency for AI workloads.
AI Products & Creative Apps
Not another thin wrapper. We design and ship defensible, vertical AI products — with the evals, guardrails, and human-centered interfaces that turn a promising demo into something a roadmap can stand on.
What we build
- —Vertical AI products & data engines
- —Retrieval & evaluation pipelines
- —Production guardrails & safe fallbacks
- —Human-in-the-loop review interfaces
- —Creative, intelligent applications
- —Feedback loops that compound over time
How we build
- 01FrameDefine the job to be done and what defensibility means here.
- 02PrototypeProve the hard 20% — evals, edge cases, the unhappy path.
- 03ShipBuild the polished, integrated product, not a demo.
- 04ImproveCapture corrections and outcomes so the product gets better.
Why Thin LLM Wrappers Fail in Production
The demo works. Then real users arrive. Here is what separates a defensible AI product from a prompt with a logo.
Products · 5 min readDesigning AI Products People Actually Trust
Trust is a design problem as much as a model problem. Patterns for interfaces that make AI legible, correctable, and safe.
Ready to forge your system?
Tell us your architecture, your constraints, and your goals. We'll come back with a clear path — not a sales pitch.