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B. Jackson — AI Enablement Pitch
Tiered K/K founding-rate pitch for AI Enablement product line
Version 1 · June 29, 2026
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# B. Jackson — AI Enablement Pitch _Parent: B. Jackson_ **Status:** Pitch drafted · Initial conversation pending **Owner:** _(TBD)_ **Deal value:** $32,000 (Standard) or $42,000 (Full) · founding rate **Timeline:** 30 days **Service category:** AI Enablement *(new product line)* > **Product-line note:** This engagement is **not** Confluxion's standard $47K Foundation + Workflow Build. It's a separate AI Enablement product designed for utility contractors with carrier-NDA exposure. ## The pitch in one sentence Bring AI to the field, safely — a 30-day engagement to govern, train, and deploy AI across civil, telecom, and power crews without leaking carrier data, breaking NDA, or letting a hallucinated load calc reach a pole. ## The three phases | Phase | Weeks | Deliverable | |---|---|---| | **Setup & Governance** | 1-2 | Signed AI use policy + tenant live + admin runbook | | **Executive Training** | 2 | 4-hour leadership working session + final policy approval | | **General Team Training** | 3-4 | Per-role training (foremen, dispatch, locators, splicers, traffic-control, estimating) + recorded library + reference cards | ## Tiered pricing — founding rate ### Founding — Standard · $32,000 Everything you need to be defensible. - Signed AI use policy — carrier-NDA reviewed - Approved-tools list + redline matrix - Per-role training (up to 60 crew) - Recorded video library + per-role reference cards - **Audit-ready binder** (physical + digital) - **Carrier-NDA cover letter** for AT&T / Verizon / Lumen - **Broker briefing + 3-question doc** for GL/E&O renewal conversation - 2-week post-training office hours ### Founding — Full · $42,000 Everything in Standard, **plus** the year-one compounding wins. - **Custom AI agent** — one workflow (DFR cleanup / RFI drafting / estimating narratives) built into their tenant - **Year-1 quarterly office hours** (instead of 2 weeks) - **60-day AI hotline** — same-day "is this OK to paste?" answers - **Quarterly peer benchmark** — year 1 free **Most contractors pick Full** — the custom AI agent is the single biggest differentiator and pays for the $10K bump inside one quarter. ## Why founding rate First three utility contractors get this pricing in exchange for permission to use the work as a public reference. Standard scope returns to **$60K market** after that. ## Payment & overage - **50% at kickoff** (signed agreement + tenant access granted) - **50% at acceptance** (policy signed, all training delivered) - **Overage:** $233 per seat past 60 crew, no markup - **Proposal good:** 60 days from issue ## ROI framing **Story 1 — incident avoidance (the safety net):** - $80K-$250K per AI-caused incident (property damage, MSA breach penalty, legal + audit defense, denied insurance claim) - $32K is less than the legal fees alone on a single contract breach - Even one incident avoided = positive ROI **Story 2 — recurring labor savings (the actual return):** - DFR cleanup: 10 min/crew/day × 30 crews = $120K+/year recovered - Office drafting: 5 hrs/week × 12 staff = $150K/year - Estimating narratives: 8 hrs/bid × 30 bids = $18K/year - Year-1 return: 6-12× the engagement cost **Market anchor:** Comparable scope at a specialty consultancy or law-firm AI advisory group runs **$60-100K**. Our founding rate is roughly half market. ## What makes this impossible to compare-shop 1. **Custom AI agent** built into their tenant (Full tier only) 2. **Carrier-NDA cover letter** addressed to AT&T / Verizon / Lumen 3. **Audit-ready binder** with signed policy + tools list + escalation chart + training rosters 4. **Broker briefing** with the 3 specific questions to ask before GL/E&O renewal 5. **Quarterly peer benchmark** (Full tier only) ## Notes for the next call - Lead with the fear-monger headline: *"Your crews are already using AI. Is it breaching your contracts — and you don't even know?"* - Anchor the price against the $60-100K market rate **before** showing tier tiles - Walk through both tiers — let them ask "which one" before recommending Full --- _Last updated: 2026-05-24_
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