The process
Diagnose. Build. Prove.
Before you invest in AI, find the workflow where it will actually pay you back. Every engagement follows the same disciplined sequence — three phases, a defined risk envelope, and a human review gate at every consequential step.
Tip: click any node for a short explanation.
Find the workflow that pays back
We map your real workflows, score each one on payback potential versus risk and effort, and pick the single workflow where AI is most likely to move a real number. Output: a Workflow Blueprint with the scope, success metric, risk envelope and rollback plan.
Safe by design, inside the envelope
We build the chosen workflow inside one of three Risk Envelope layers — Safe Start, Controlled Workflow or Deeper Integration. Audit log, rollback and a human in the loop are wired in from day one. We start as conservative as the workflow needs.
Prove it pays before scaling
The workflow is piloted in shadow mode, measured against the agreed success metric and hardened — monitoring, permissions, kill-switch. Only then does it get promoted to production, or adjusted, or stopped cleanly. No sunk-cost theatre.
Safe Start
AI reads, suggests and drafts. A human still sends, files or commits every output. Zero unsupervised access to customers, money or sensitive systems.
Controlled Workflow
AI performs scoped, reversible actions inside a review queue. Permissions are narrow, every action is logged, and anything can be rolled back within minutes.
Deeper Integration
AI runs autonomously in one narrow lane — only after the lower layers have proven safe. Always logged, always monitored, always killable from a single switch.
Request a calibration call
A 30-minute conversation to identify the single workflow most likely to pay back, and the risk envelope it should be built inside. No pitch, no obligation.
- Pressure-test your top candidate workflow
- Agree the success metric that defines payback
- Pick the Risk Envelope layer that fits
- Decide whether to commission the full diagnostic