AI STUDIOSecurityEvalsHuman oversightFixed scope
Use cases
Outcome-led product work. Models and vendors are chosen to fit your constraints, not the other way around.
- In-product copilots and assistants
- Intelligent search and RAG over product data
- Customer-facing agents with tool use
- Document intelligence and extraction
- Recommendations and personalization
- Conversational product features
Who this is for
Seed-to-growth startups and product teams with something real to improve.
- Founders and CTOs without a dedicated AI engineering team
- Product leaders under pressure to launch AI features
- Teams with an existing product, users, and dataset, not just a concept
- Engineering leads who need guardrails, evals, tenancy, and cost control
How we work
Bounded phases from first call to production, no open-ended chaos.
Strategy Call
Free
Discovery Sprint
1–2 weeks · Paid
Proof of Value
3–6 weeks
Production Build
6–14 weeks
Optimize
Monthly
Proof pattern
Representative scenario, not a named client logo. Shows how product AI engagements typically ship.
Representative scenario
In-product copilot for a B2B SaaS analytics platform
Support deflection target, instrumented against “how do I…” tickets and time-to-insight
Before → after: Users opened tickets for routine workflow questions → grounded in-product answers with citations and a fail-closed handoff to support
Typical engagement length: Discovery + 4-week PoV, then phased production rollout