Why this works (public proof):

• Klarna’s AI assistant now handles ~⅔ of service chats, doing the work of ~700 FTEs, cutting resolution time from 11→2 minutes, and reducing repeat contacts by 25%. That’s governed, measurable automation in the wild. (Klarna)
• Salesforce’s CEO says AI now does ~30–50% of the company’s work; support volumes handled by agent tech have surged (Agentforce). The “agentic enterprise” is no longer theory. (Bloomberg)
• CarMax used Azure OpenAI to summarize 100k+ reviews, turning multi-year manual work into days—proof that well-scoped content/ops tasks compound fast. (Microsoft)

What we build (and why it’s safer)

A governed AI Twin for one revenue-adjacent workflow (you choose: Lead Reactivation, Proposal Follow-Up, or Collections/Ops). It drafts, you approve, it logs everything.

• Human-in-the-loop approvals via n8n’s Wait/Resume URL (one-click Approve/Reject). No auto-sending. (n8n Docs)
• Structured Outputs (JSON Schema) so drafts are machine-readable and dependable. (OpenAI)
• Email safety: create Gmail drafts only (or your ESP), never fire without human approval. (n8n Docs)
• Security posture: OWASP LLM Top-10 patterns (prompt-injection resistance + data boundaries). (OWASP)

The 14-Day Build (done for you)

Day 1–2 — Diagnostic & Win Pick

We map one “low-effort/high-impact” play in your funnel (Reactivation, Proposal, or Ops). You’ll see baseline KPIs and a target money slide (time saved → Net ROI). (McKinsey’s macro view supports the productivity upside; we focus on your tiny, provable slice.) (McKinsey & Company)

Day 3–7 — Build the Spine

• System prompt + guardrails, a 10-snippet Context Pack
• n8n flow: Preflight → Model (Structured JSON) → Gmail Draft → Wait for Approve/Reject → Log to Sheet/Notion (n8n Docs)
• Run-Log schema with tokens, cost, status, replies, booked calls, revenue

Day 8–10 — Pilot & Tune