New AI features, automation of manual steps, analytics for decisions, or roadmap clarity when goals are fuzzy and teams need evidence.
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AI Strategy & Roadmap turns ideas into evidence-backed initiatives. We link use cases to P&L and KPIs, map current processes, and identify high-leverage points where AI, automation, or analytics can create a measurable impact without disrupting what already works.
Through rapid discovery, stakeholder workshops, and a light data/tech assessment, we evaluate desirability, feasibility, and viability. We review risks and compliance, compare model/provider options, and outline the “thin slice” you can ship first to prove value quickly.
A complete planning pack: problem statements and value hypotheses, KPI tree and baselines, target users and journeys, PRD with acceptance criteria, prioritized backlog (RICE/WSJF), estimates, and dependencies—ready for engineering handoff.
We build in governance from day one—privacy, security, and responsible AI guardrails—with change management steps so teams adopt new flows. Dashboards, OKRs, and review cadences keep outcomes visible and decisions auditable as you scale.
New AI features, automation of manual steps, analytics for decisions, or roadmap clarity when goals are fuzzy and teams need evidence.
Typically, two weeks for discovery and analysis; one to two more for PRD, estimates, and the 90-day roadmap.
No. We assess data readiness and model options, then recommend a thin slice that can be shipped using existing systems first.
We model value against baselines, cost per task, and risk controls; run sensitivity scenarios; and set checkpoints before scale-up.
Product, design, engineering, data/ML, security/compliance, finance, and a business owner—plus a small customer panel for validation.
We transition into build with feature flags, evaluations, and telemetry—launching a production pilot within 8–12 weeks.
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