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hmtech.one — AI-Readiness Audit Strategy

Date: 2026-04-26

Owner: Harnoor Singh

Status: Draft v1

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One-Line Promise

> "In 14 days you'll know exactly which AI bets to take — and which ones to skip — before you waste a dollar."

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Who It's For

Sweet spot: $5M–$100M revenue, 20–300 employees, at least one person who cares about data

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Who It's NOT For

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The Differentiator vs. Big-4 / Boutique Consultancies

| Dimension | Big 4 (Deloitte/PwC/etc.) | Generic Boutique | hmtech.one |

|---|---|---|---|

| Who does the work | Junior analyst, partner on call | Mixed bag | Harnoor — senior, technical, ships code |

| Delivery time | 6–12 weeks | 4–8 weeks | 14 days |

| Price | $75K–$300K | $20K–$75K | $8,500 flat |

| Output | Framework PDFs | Slide decks | Working scorecard + prioritized roadmap with effort estimates |

| AI stack depth | Strategy-layer only | Varies | Kafka, Flink, Iceberg, dbt, Spark, Claude, AWS — hands-on |

| Follow-on | Expensive retainer | More projects | Optional, bounded, priced transparently |

| Vendor neutrality | None (partner ecosystems) | Mixed | 100% — no referral fees, no reseller agreements |

The core pitch: You get the senior person, not the person who sold you the senior person. Harnoor has built and run live AI systems (TITAN, Silent Infinity) — the audit output reflects actual build experience, not framework slides.

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Offer Ladder

Tier 0 — Free: AI Readiness Score Call (30 min)

Tier 1 — Paid: 2-Week AI Readiness Audit ($8,500 flat)

Tier 2 — 90-Day Implementation Retainer ($4,500/month)

Tier 3 — Fractional CAIO Retainer ($6,500/month)

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The Audit Deliverable — What the Buyer Literally Receives

What's delivered at Day 14:

1. AI Readiness Scorecard (PDF + interactive Google Sheet)

2. Findings Report (PDF, 15–25 pages)

3. Prioritized 90-Day Roadmap (1-page visual + supporting detail)

4. Executive Readout (live 90-min video call)

5. Vendor Shortlist (if applicable)

6. 30-Day Access Window

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3 ICP Profiles

ICP 1 — The Overwhelmed CTO at a Services Business

Company: 50–150 person professional services firm (agency, staffing, logistics, healthcare admin)

Pain: Vendors are pitching AI every week. The CTO can't tell real from hype. Their data is scattered across 4 systems. They've spent $40K on a "data warehouse" that nobody uses. The CEO keeps asking "what's our AI strategy" and the CTO doesn't have an answer.

Job-to-be-done: Get a credible, defensible answer to the CEO in writing — fast.

Pitch line: "You need to go into that board meeting with a real answer. In 14 days, you'll have a written scorecard, a 3-priority roadmap, and an exec-ready summary — built by someone who's actually wired AI into production systems."

ICP 2 — The Growth-Stage CEO Who Wants Efficiency

Company: 20–80 person SaaS or e-commerce company, $5M–$30M ARR, scaling fast, costs are climbing

Pain: The team is drowning in manual ops. Customer support is a bottleneck. Sales ops runs on spreadsheets. The CEO knows AI can fix some of this but doesn't know what to build, buy, or ignore. They've looked at ChatGPT — it impressed them but they don't know what to do with it at a systems level.

Job-to-be-done: Identify the 2–3 specific workflows where AI cuts headcount cost or improves throughput — with concrete next steps.

Pitch line: "Tell me your three messiest workflows. I'll tell you which ones AI can actually fix this quarter and which ones you should leave alone — then I'll build a roadmap to prove it."

ICP 3 — The Mid-Market Data Leader Preparing for an AI Initiative

Company: 200–500 person company, has a data team (2–6 people), has BI tooling (Tableau/Looker/Power BI), leadership is asking for AI but the data team knows the infrastructure isn't ready

Pain: They're caught between leadership hype and data reality. They need an independent, technically credible assessment they can present upward to justify infrastructure investment — or push back on unrealistic timelines.

Job-to-be-done: Independent validation of their read on the data landscape + a written roadmap they can present to leadership.

Pitch line: "You already know what's broken. What you need is someone external to say it in writing — credibly, technically, and without a vested interest in selling you software."

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Distribution Plan

Channel 1 — LinkedIn (Primary, Weekly Cadence)

Goal: 2–3 inbound leads/month from content by month 3

Content pillars (rotate weekly):

1. "AI Audit Finding" post — one real observation from the field (anonymized), framed as a pattern ("The #1 data problem I see at 50-person companies is...")

2. "Quick Win" post — a specific AI use case that's underrated, with effort/cost estimate

3. "Myth Bust" post — one AI claim that's overhyped, explained plainly

4. "Process post" — behind-the-scenes of how the audit works (builds credibility)

Format: Text-first, no stock images, occasional 1-page visual. 300–600 words. End every post with a soft CTA ("DM me 'audit' if you want to talk through your situation").

Target profile: Post from Harnoor's personal LinkedIn, not a company page. People buy from people.

Cadence: 3 posts/week Mon/Wed/Fri. 30 min engagement after each post (comment replies build algorithmic reach).

Channel 2 — Cold Outbound via LinkedIn DM (Precision, Not Volume)

Goal: 5 qualified conversations/month from 50 outreach contacts

Method:

> "Hey [name] — saw your post about [specific topic]. I run AI readiness audits for [type of company]. Most of the CTOs I talk to are stuck at the same place: they know they need to move on AI but can't figure out where to start without wasting budget. Worth a 30-min call?"

Volume: 50 DMs/week = ~6–10 replies = ~2–3 calls = ~1 qualified lead per week

Channel 3 — Community + Events (Compound Value)

Goal: 1–2 client referrals/quarter; 1 speaking slot/quarter by month 6

Targets:

Forum play: Answer 2–3 questions per week in target communities about AI strategy, data infrastructure, or "where to start with AI." No hard pitching — value first. Profile links back to hmtech.one.

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30/60/90-Day Plan

Days 1–30: Launch + First Revenue

What ships:

Test: Can you sell the audit to 1 buyer from your existing network in 30 days?

Target: 1 paid audit ($8,500), 5 score calls, 50 LinkedIn followers gained

Days 31–60: Prove + Refine

What ships:

Test: Does the case study convert to 1–2 inbound inquiries?

Target: 2 paid audits ($17K), 2 retainer conversations opened, 1 testimonial captured

Days 61–90: Scale + Productize

What ships:

Target: 3 audits sold total ($25,500), 1 retainer active ($4,500 MRR), break-even on first 90 days

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Risks + Mitigations

Risk 1 — Commoditization / Race to Bottom

The threat: By Q3 2026, every freelance consultant will offer an "AI audit." The market fills with $2K–$3K versions from offshore generalists.

Mitigation: Differentiate on three things that can't be commoditized: (1) real technical depth in the actual AI stack (Kafka, Flink, Claude API, AWS), (2) speed (14 days, not 6 weeks), (3) Harnoor's name and reputation (not a faceless agency). Publish work openly. The audit is the demonstration of expertise, not just a deliverable.

Risk 2 — Scope Creep

The threat: Clients want "just a little more" after the audit is delivered. Free consulting hours eat margin.

Mitigation: Hard 30-day access window. All new requests go to Tier 2 SOW. The SOW template defines scope explicitly. On the discovery call, say explicitly: "The audit is scoped to exactly what's in the SOW. Anything beyond that is a separate engagement."

Risk 3 — Brand Confusion (TITAN / Silent Infinity)

The threat: If Harnoor mentions TITAN or Silent Infinity on sales calls, buyers get confused about what they're actually buying.

Mitigation: hmtech.one is a standalone brand. TITAN is internal infrastructure. Silent Infinity is a separate product. Never mention either in hmtech.one marketing. If a prospect asks "what else do you build?" the answer is: "AI systems for my own research — which is where the practical knowledge comes from. hmtech.one is where I apply it for clients."

Risk 4 — No-Show / Tire-Kicker Score Calls

The threat: Free calls attract people who aren't buyers. Time burns, no revenue.

Mitigation: Pre-call intake form (5 questions including company size, what they've tried, and what a win looks like in 90 days). Anyone who doesn't complete the form doesn't get the call. Optionally add a $150 "seat deposit" refundable on audit purchase — kills tire-kickers instantly.

Risk 5 — Single Point of Failure (You)

The threat: Harnoor gets sick, lands a full-time role, or gets overloaded. All revenue stops.

Mitigation: Cap at 3 active audits simultaneously. Keep retainer load under 2 active clients. This is a lifestyle-scaled business, not a venture-scaled one. Revenue ceiling at this structure: ~$25K/month (3 audits + 2 retainers). That's the goal, not a risk.

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Pricing Test Grid

Recommended Starting Anchor: $8,500 (Tier 1 Audit)

| Variant | Scope | Price | Test Signal |

|---|---|---|---|

| Anchor | Full 14-day audit, 5-dimension scorecard, roadmap, exec readout | $8,500 | Baseline conversion rate |

| Premium | Same + 60-day implementation sprint (top 1 use case built) | $18,500 | How many upgrade when bundled? |

| Entry | Rapid 5-day "AI Signal Scan" — data infrastructure + top 3 use cases only, no exec readout | $3,500 | Lead gen, price-sensitive buyers |

| Retainer Add-On | 90-day implementation at audit completion | +$4,500/mo | Attach rate from audit buyers |

| CAIO Retainer | Strategic only, no implementation | $6,500/mo | Appetite for ongoing advisory |

Pricing rationale:

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Sources (Market Research)