Own Lead Quality Prediction AI.

What you'd own.

Every artifact below transfers to your accounts on day one. The whole engine.

• ●Founder persona and cold-outbound GTM playbook targeting VP Sales
• ●LinkedIn sequence templates and objection handling frameworks
• ●ML lead-scoring model architecture and training pipeline design
• ●CRM integration specifications for Salesforce, HubSpot, Pipedrive
• ●Financial model and unit economics to 150k ARR target
• ●Brand identity, tagline, and landing page copy
• ●Customer onboarding and success process documentation

What Roll Digital builds for you.

Custom scope to take Lead Quality Prediction AI from MVP shell to operating business.

• ▸Production ML inference API with Postgres historical data store
• ▸CRM connectors with OAuth for Salesforce, HubSpot, Pipedrive
• ▸Trial user flow: sign up, CRM import, first predictions
• ▸Stripe billing for three pricing tiers up to 249/month
• ▸Email sign-in and Google OAuth authentication with password recovery
• ▸Lead scoring dashboard with confidence scores and model metadata
• ▸Sales rep feedback loop to track prediction accuracy
• ▸Initial 30-day customer onboarding with weekly success check-ins

Why this could work.

The GTM is repeatable: VP Sales and RevOps leaders at 10-100 person SaaS companies actively seek lead-scoring tools. The TAM is substantial, with 150k SMBs spending 1800 annually on standalone solutions. If the model works on each customer's data, switching costs are high once integrated into daily sales workflow. Cold outbound to a self-identified pain point has a low CAC profile and proven strong trial-to-paid conversion.

What you'd risk.

HubSpot and Salesforce bundle lead scoring into tiers most targets already pay for, collapsing standalone value instantly. Model accuracy lives entirely on each customer's historical data quality, and most SMBs have sparse, inconsistent deal logs that produce useless predictions within weeks. Sales reps resist AI gatekeeping their pipeline. Retention requires flawless accuracy or constant engagement, making churn likely without tight feedback loops.

Who this fits.

An experienced SaaS operator or sales consultant with existing relationships in the 10-100 person company space. You need cold-outbound execution chops, understand CAC/LTV mechanics, and can handle technical founder responsibilities. Ideal fit: someone who worked at a RevOps tool or consulted for SMB sales teams, with operational stamina to manage tight feedback loops and model iteration.

Timeline.

From contract signing to operating business.

1. Day 1
   Receive product specs, business model docs, brand assets
2. Week 1
   ML inference API operational, Postgres database configured
3. Week 3
   CRM connectors live, free trial import flow working
4. Week 6
   Billing and auth complete, first outbound campaign sent
5. Day 90
   First paid customers onboarded, feedback loop gathering data

Pricing.

Three ways in, depending on how much you want to build yourself.