Client Overview
- Type of AI company: Vertical GenAI platform for legal ops automation (AI agents for contract review and litigation workflows)
- Stage: Pre-seed, technical founding team
- Buyers: Mid-sized law firms, in-house legal teams, legal ops execs
- Revenue motion: Founder-led → sales-assisted hybrid motion (non-PLG)
Role & Duration
Role: Founding GTM Architect — embedded from Day 1
Duration: 3 months (0→1 architecture), retained through scale phase
The challenge
They had a brilliant product demo — an AI agent that could analyze a contract, spot risk clauses, and auto-draft redlines in seconds.
It blew people away.
But no one knew how to buy it.
- Buyers loved the idea — but didn’t trust the AI to operate in real workflows
- Product was positioned as a legal co-pilot, but pricing and delivery were fuzzy
- Sales cycles died in legal review or procurement hell
- Every inbound was bespoke; no repeatability, no segmentation
- Product market fit signals were latent, but unconverted
This wasn’t a marketing problem.
It was a commercial system gap — no positioning, no sales design, no structured path to revenue.
Strategic & operational approach
1. Architected the GTM model before a single lead closed
The day I stepped in, the founders were demoing to anyone who’d take a call. We stopped that immediately.
Instead, we:
- Identified three core ICPs by pain intensity, not persona titles
- Prioritized one vertical: mid-sized U.S. firms with stretched legal ops and high-volume contract flow
- Mapped the internal buyer chain: legal ops → partner → IT/security
- Framed the product not as “AI for legal,” but as a revenue shield — cutting redline cycles by 3x without hiring more associates
This wasn’t just messaging. It informed the entire go-to-market chassis.
2. Built the offer, price, and sales experience from zero
No one knew how to evaluate a GenAI agent inside legal. So we engineered a trust-first offer strategy:
- Designed a 2-week test pilot scoped around one painful workflow (e.g., NDAs or SaaS agreements)
- Bundled it with pre-built prompt templates + white-glove onboarding
- Priced it at $8K flat with guaranteed time savings backed by proof
We then created a 3-tier offer model:
- Test → Embed → Expand
- Each stage had clear ROI, support, and outcome metrics baked in
No free trials. No open-ended pilots.
Just controlled exposure that proved value fast.
3. Created a GTM stack designed for speed + signal
We deployed the first version of the GTM stack in week 2:
- High-trust landing page with vertical proof points and use-case videos
- ROI calculator based on clause volume and redline cycles
- Deal desk system that handled security objections, pilot briefs, and rollout paths
We also ran outbound in parallel:
- Built an account list based on contract workload, deal velocity, and firm size
- Cold messaging focused on cost-per-redline — the real pain metric
- Nurture flow included legal-specific proof, pilot case briefs, and objection crushers
We moved from awareness to signed pilot in 6 days on the first outbound wave.
4. Aligned product and sales motion for credibility
To prevent the AI skepticism death spiral, we:
- Created demo environments scoped to real documents by vertical
- Aligned AI outputs to legal language norms and jurisdictional triggers
- Built an internal playbook for founder-led sales: from discovery → co-pilot mapping → compliance handling
Every touchpoint was designed to build technical and professional trust — without slowing down the cycle.
Results & business impact
- Closed $150K in ARR from cold leads in 60 days
- Converted 4 out of 6 pilot accounts to multi-seat annual contracts
- Reduced sales cycle from 41 to 12 days
- Achieved 73% demo-to-pilot conversion
- Productized the offer into a repeatable sales motion now run by a non-founder team
This was GTM that shipped with the product — not bolted on after the fact.
Why working with me was the advantage
This team didn’t need demand gen.
They needed a system that could sell what they’d actually built — to buyers who don’t trust buzzwords and won’t take risks without clear ROI.
What made this work:
- We built around real buyer psychology — not founder assumptions
- We scoped the offer to maximize signal, not just show off features
- We matched narrative, price, and delivery to the speed of trust
Most AI startups burn 6 months trying to retro-fit PLG or spray demos to anyone with a LinkedIn.
We went the opposite way: tight, vertical, painful problem → proof → revenue.
If you’re building an AI-native platform and tired of playing sales roulette, I’ll build the GTM system that earns trust, closes deals, and compounds traction.
From day zero — to revenue.
And I don’t stop until it performs.