Co-build AI-native products that win enterprise deals.
We co-build AI-first SaaS and agentic systems for founding teams selling into regulated buyers. Multimodal workflows, production platforms, and a team that thinks past the codebase — into onboarding, pilots, and security reviews.
The demo lands. The enterprise pilot doesn’t.
Enterprise security review blocks the deal
SOC 2 evidence, data-flow diagrams, prompt logging, model-card disclosure, residency commitments — every enterprise buyer asks. Founding teams ship the demo and stall at the questionnaire.
Hero-engineer dependency
One founding engineer holds the prompt graph, the eval set, the deploy keys. The day they go on leave, the velocity goes with them — and the codebase is unreadable to the next hire.
No evaluation, no defensibility
Without an eval harness and a regression set, every model bump is a coin flip. Enterprise pilots want to see how you measure quality — vibes don't pass procurement.
Demo-to-deploy gap
The Loom looks great. Production has rate limits, retries, prompt drift, observability, fallback paths, and a runbook. The gap between the two is where the timeline slips and the deal goes cold.
Design-partner sprawl
Five logos, five custom integrations, five Slack channels, five different success criteria. Pilots become bespoke forks — and the product roadmap stops being a product.
Engineering past the codebase — into the deal flow.
AI-native platform engineering
Multi-tenant inference, prompt versioning, vector stores, retrieval pipelines, model gateways — the platform layer that lets the product team ship features instead of plumbing.
Agentic system architecture
Tool-using agents, structured workflows, function-calling orchestration, human-in-the-loop checkpoints — designed to act inside your customers' systems, not just chat about them.
Evaluation harnesses
Golden sets, regression suites, LLM-as-judge with calibration, red-team libraries — built so every model bump and prompt change has a measured answer, not a vibe check.
Enterprise security checklists
SOC 2 evidence, data-flow diagrams, residency posture, prompt logging, PII handling, model-card disclosure — the artefacts that get you through procurement, packaged in a data room.
Design-partner onboarding
Onboarding flows, sample-data pipelines, eval rubrics co-defined with the buyer, white-glove success criteria — design partners that turn into reference customers, not custom forks.
Pilot-to-paid playbook
Pilot scoping, success-metric definition, exit criteria, contract handoff, security-review pack — the operational rail that takes a free trial to a signed enterprise contract.
Sprint, pod, or retainer — sized to your runway.
Founding-team sprint
Practitioners alongside the founders — model selection, eval design, security posture, architecture review. We leave with a costed plan and an enterprise-ready roadmap.
- ·Co-built with founders
- ·Eval + security posture defined
- ·Costed roadmap to enterprise
Full pod
A complete co-build pod — engineering, ML, MLOps, evaluation — shipping into your repo, your sprints, your release train. Production targets, security artefacts, and pilot playbooks delivered.
- ·Pod into your repo
- ·Security artefacts shipped
- ·Pilot-to-paid playbook
Fractional CTO support
Senior practitioner on retainer — architecture reviews, hiring panels, security-review escalations, board-level technical narrative. Available when the deal hangs on a technical answer.
- ·Senior practitioner on retainer
- ·Architecture + hiring reviews
- ·Board-level technical narrative
Where else we ship for founders.
Applied & Generative AI
Practitioner-led consulting from data policies to production agents — strategy, platform, applied solutions, evals, and operations under one team.
Digital Products & Platforms
Production-grade product engineering and platform builds for digital businesses — design, delivery, and operations under one team.
AI Talent
Production AI practitioners ready to embed into your team — engineers who have shipped AI into regulated estates.