Product AI roadmap
Decide which AI features belong in the product and in what order.
- 1Maps features to customer jobs
- 2Estimates inference cost per user
- 3Sequences releases by value
San Francisco, CA · AI Strategy & Consulting
An AI roadmap for San Francisco companies that separates the features customers will pay for from the ones that only demo well, with build-versus-buy decisions made on evidence.
AI Strategy & Consulting in San Francisco
San Francisco builds the tools everyone else adopts: SaaS platforms, fintech, biotech and the startups around them. Teams here move fast on AI, so the hard part is rarely the demo. It is evaluation, cost, security review and shipping to real customers.
Where it fits
Decide which AI features belong in the product and in what order.
Model approval and monitoring that banking partners will ask about.
Separate real research speed-ups from expensive experiments.
Built for California rules
Notice, opt-outs and data minimisation for personal data AI uses.
Risk assessments, pre-use notices and opt-outs for automated decisions.
Anti-bias testing and records for AI used in hiring and promotion.
Stricter-than-HIPAA limits on sharing medical information.
A written security program covering every system that handles customer financial data.
Working together · Pacific Time
Your early morning is our late evening, so we meet live as your day starts and build while you sleep.
How we work
We learn your goals, constraints and the processes that matter most.
We run discovery sessions and review your data and systems.
We score use cases on value, feasibility and risk, together with you.
We hand over a roadmap, and can stay on to deliver the first phase.
Often yes. Many San Francisco teams have several AI tools bought team by team. We map what is in use, what it costs and where it overlaps, then decide what to keep, consolidate or build.
Yes. Any use case that makes or shapes a significant decision about people is flagged early, so risk assessments and opt-outs are planned and costed rather than discovered at launch.
A prioritised list of AI use cases, a readiness assessment covering data, systems, skills and governance, and a phased roadmap with the decisions and investment each phase needs.
No. Part of the work is finding out what state your data is in and what it needs for each use case. Many useful AI projects can start with the data you already have.
Yes. The same team designs and delivers agentic AI, generative AI, data platforms and applications, so the roadmap moves straight into delivery without a hand-off.
Let's talk
We help you navigate Enterprise AI, from first use case to production.
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