Find high‑leverage AI wedges. Pilot fast. Prove ROI. Scale with governance.
Most teams want AI in the product and org—few know where it pays back first. We help you pick the right problems, validate quickly, and scale responsibly.
Where AI Can Pay Back
Product: personalization, recommendations, in‑app copilots, retrieval/summarization
Growth: lead scoring, lifecycle comms, creative ops
Ops: support deflection, agent‑assist, QA automation, risk triage
Engineering: internal copilots, test generation, incident postmortems
We prioritize impact × feasibility × time‑to‑value—not AI theater.
How We Work
1) Wedge Sprint (2 weeks)
- Opportunity map → ROI stack‑rank
- Baselines & success criteria
- Technical approach (build vs buy; LLM/RAG vs rules)
Deliverable: AI Wedge Plan (top 2–3 bets, metrics, owners, timeline)
2) Pilot & Prove (4–8 weeks)
- Build pilot on real users/ops
- Instrumentation + A/B or pre/post
- Cost model & guardrails
Deliverable: Pilot Report (uplift, cost/benefit, go/no‑go)
3) Scale & Govern (quarterly)
- Rollout playbook, data/PII policy, human‑in‑the‑loop
- Evals, drift checks, reliability and rollback
Deliverable: AI Operating Guide (KPIs, review cadence, risks)
Metrics We Hold Ourselves To
Product: ↑activation/retention, ↑conversion, ↓time‑to‑value
Ops: ↓AHT, ↑FCR, ↑deflection, ↓cost/ticket
Eng: ↓cycle time, ↑coverage, ↓incidents, ↑dev satisfaction
Finance: uplift per ₹ spent, breakeven timeline
What You Get
- AI Wedge Plan (prioritized use‑cases with ROI)
- Pilot build to decision
- Evaluation harness (quality, hallucination, safety, cost)
- Governance (data policy, review cadence, rollback)
Engagement Models
Wedge Sprint (2 wks) · Pilot & Prove (4–8 wks) · Scale & Govern (quarterly)