Own Sales Stage Predictor AI.

What you'd own.

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

• ●Brand identity, positioning narrative, and landing page for Sales Stage Predictor AI.
• ●Trained AI model for deal stage prediction and inference pipeline.
• ●CRM OAuth integrations for Salesforce and HubSpot with API architecture.
• ●LinkedIn outbound playbook and messaging templates for RevOps buyer targeting.
• ●Financial model, pricing framework, and unit economics for three pricing tiers.
• ●Founder insights into RevOps buyer motivation and multi-rep adoption challenges.
• ●MVP product, database schema, and deployment infrastructure on production-ready stack.

What Roll Digital builds for you.

Custom scope to take Sales Stage Predictor AI from MVP shell to operating business.

• ▸Production backend on FastAPI or Node.js with Postgres relational database.
• ▸Multi-tenant auth: email login, SSO, and OAuth with CRM platforms.
• ▸Stripe billing integration across three pricing tiers with usage metering.
• ▸Real-time CRM data sync and webhook handlers for Salesforce and HubSpot.
• ▸AI inference pipeline with monitoring, accuracy scoring, and confidence percentiles.
• ▸Custom domain provisioning, SSL certification, and DNS routing for white-label accounts.
• ▸Onboarding flow: CRM OAuth, data validation, and 14-day trial activation.
• ▸Customer success playbook and 30-day support for first cohort trials.

Why this could work.

Fifty thousand underserved SMB companies with active sales teams need deal-stage automation without Clari-scale pricing. RevOps directors at 50-300-person firms are proven buyers of sales automation. CRM OAuth provides frictionless onboarding. Fourteen-day trials with warm accounts can show ROI fast. If prediction accuracy stays strong on healthy pipelines, conversion and retention become viable. Market timing favors embedded AI over standalone tools.

What you'd risk.

Salesforce Einstein, HubSpot Breeze, and Clari ship native deal-stage AI every quarter. Differentiation is fragile and shrinking. Prediction confidence collapses on new customers with sparse or dirty pipeline data; they churn within two weeks. Sales reps routinely override AI labels when gut feel differs. Without enforced manager adoption, usage stagnates and NRR craters. The 14 percent success rate reflects genuine competitive and adoption headwinds.

Who this fits.

An operator with prior SaaS or sales software experience, ideally with warm RevOps relationships at mid-market companies. Technical depth required to navigate CRM partnerships. Must be comfortable with adoption challenges and month-by-month churn iteration. A prior founder or sales operations leader with a warm network is strongest fit. Solo founder starting cold will face steep customer acquisition cost without industry connections.

Timeline.

From contract signing to operating business.

1. Day 1
   Access to founder, codebase, customer list, and AI model training process.
2. Week 1
   Production infrastructure live on FastAPI/Postgres, multi-tenant auth complete and tested.
3. Week 3
   Stripe billing operational, three pricing tiers live, first test account onboarded.
4. Week 6
   Customer OAuth connect verified working, real CRM data syncing, first predictions live.
5. Day 90
   Minimum 5-10 trial accounts active, prediction accuracy baseline established, churn rate measured.

Pricing.

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