Playbooks
How to ship without guessing
Practical execution sequences: readiness baselines, governance, cost and reliability operations, and rollout cadence.
Playbook
Are You Ready for AI in Production?
Before you build, confirm data quality, workflow ownership, and governance. Then prioritize use cases by value and risk.
Typical timeline
2 to 3 weeks for baseline assessment and prioritized roadmap.
Playbook
From AI Pilot to Production in 90 Days
Use a 90-day gated rollout: baseline and evals first, harden next, then launch only if reliability, risk, and adoption thresholds pass.
Typical timeline
90-day execution model: Foundation (weeks 1 to 2), Pilot hardening (weeks 3 to 6), Controlled rollout (weeks 7 to 10), Production cutover (weeks 11 to 13).
Playbook
Where AI Stops and Humans Decide
Set clear handoff rules: automate low-risk actions, and require human review for high-risk or irreversible decisions.
Typical timeline
3 to 5 weeks to define policy matrix and review orchestration.
Playbook
Run AI Models Cheaply and Reliably
Route requests by intent, use caching, and define fallbacks so cost stays predictable without sacrificing quality.
Typical timeline
4-week implementation baseline plus ongoing tuning cadence.