AI Product Development
Ship reliable AI products—pilot to production in weeks.
Senior teams that design, build, and run AI software. We wire guardrails, evals, and observability from the start—so launches are fast, safe, and measurable.
Cycle time (pilot → prod)
8 weeks
Typical end-to-end
Reliability
99.9%
SLO with guardrails
Eval pass rate
96%
Quality & policy checks
Guardrails-first
Policy checks, redaction, and allow-lists before actions.
Observable by default
Traces, prompts, costs, and regressions tracked nightly.
Model-agnostic
Use the right model per task—LLM, embedding, vision, or custom.
Config not code
Versioned prompts, routes, and evals as config.
Live engineering dashboards
Track delivery, quality, and reliability—wired to your repos, runs, and evals.
Delivery health
Lead time (days)
Design → PrototypeAfter 5 / Before 12
Prototype → BetaAfter 6 / Before 10
Beta → GAAfter 8 / Before 14
Deployment frequency
Quality & safety
Automated evals
96%
Policy & accuracy
Hallucination checks94%
PII redaction98%
Toxicity filter99%
Incidents (30d)
CriticalAfter 1 / Before 4
HighAfter 2 / Before 7
MediumAfter 5 / Before 12
Latency & cost
p95 latency (ms)
Cost per 1k calls (index)
How we ship
A clear, week-based plan—from alignment to scale.
Align
Scope goals, success metrics, constraints, and data sources.
Prototype
Working slice with evals and guardrails in Week 2.
Integrate
Wire to systems (APIs, DB, auth) with versioned configs.
Harden
Load tests, red-team prompts, policy checks, and SLAs.
Deploy
Blue/green or canary with rollback and audit trails.
Observe
Traces, costs, regressions; nightly tests and alerts.
Fits your stack
Ship where you work. CI/CD, observability, and data already connected.
Jira
Linear
GitHub
GitLab
Figma
Slack
Datadog
Sentry
Segment
PostHog
AWS
GCP
Azure
Vercel
Snowflake
BigQuery
Custom APIs
Ready to build your AI product?
Get a working slice in weeks—not months. Tell us your goals.