- Industry
- SaaS (B2B)
- Engagement length
- 16 weeks
- Milestones delivered
- M1 Map, M2 Build & Deploy, M3 Prove, M4 Expand
- Stack
- Existing CRM + custom AI operator (read/write via API)
Discover
We measured how reps spent qualification time and scored the workflow on the Leverage Map. Inbound qualification was high-impact and high-readiness, a clean first milestone.
M1 · Map
The spec defined the qualification rubric, the CRM data contract, the escalation rule for ambiguous leads, and the metric: qualified pipeline per rep versus the Discover baseline.
Plotted workflows (Readiness, Impact): Exception triage (78, 84) Automate First, the M1 candidate; Carrier comms (44, 72) Prove the Case, graduating to (66, 76) after Milestone 1; POD reconciliation (70, 40) Quick Wins; Detention flagging (36, 30) Park / Revisit.
M2 · Build & Deploy
The operator ran inside the CRM the reps already used, scoring and enriching inbound leads, and handing borderline cases to a human with its reasoning attached.
M3 · Prove
Qualified pipeline per rep rose 4.2× against the baseline, measured over the agreed window.
4.2×
qualified pipeline per rep vs. baseline
Expand
Support deflection was re-scored into Automate First and shipped as the next milestone, and the rail extended.