Own LinkedIn Safe-Harbor IP Scorer.

What you'd own.

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

• ●Live IP restriction detection algorithm trained on LinkedIn automation data
• ●Residential proxy provider partnership agreements and integration templates
• ●Outreach playbooks targeting Reddit, Slack, and automation community channels
• ●Early customer list and monetization data from beta period
• ●Landing page, brand positioning, and pricing tier framework
• ●Founder research on buyer behavior and proxy spending patterns

What Roll Digital builds for you.

Custom scope to take LinkedIn Safe-Harbor IP Scorer from MVP shell to operating business.

• ▸Production backend on FastAPI with Postgres for real-time IP monitoring
• ▸Stripe billing system supporting three subscription tiers and annual plans
• ▸API and embedding widgets for residential proxy provider dashboards
• ▸Multi-tenant auth system with email and OAuth sign-in
• ▸Admin dashboard showing restriction rates, trends, and proxy provider rankings
• ▸Automated notification system when IP quality degrades for users
• ▸Initial 30-day customer success and onboarding support

Why this could work.

The target audience is specific and cash-rich: 25,000 serious LinkedIn automators spend $340 annually on IP quality tools. Direct outreach to Reddit and Slack automation communities bypasses LinkedIn ToS restrictions on self-promotion. Residential proxy providers need embedded IP scoring as a value-add, creating built-in distribution partners. You establish a data moat by accumulating the largest crowdsourced IP restriction dataset. TAM is real and measurable.

What you'd risk.

LinkedIn continuously evolves its detection methodology beyond IP signals, making pure IP-block scoring potentially irrelevant overnight. A thin user base produces stale, unreliable crowdsourced data. You cannot market directly on LinkedIn, forcing expensive, indirect GTM. Residential proxy giants like Brightdata and IPRoyal could embed native scoring into their dashboards within months. Year 1 projects negative take-home. Customer acquisition is uncertain.

Who this fits.

Best fit for a solo SaaS founder or small team already embedded in the automation or proxy community. Ideally someone with hands-on LinkedIn automation experience and existing relationships with proxy providers or automation communities. Could be a former agency operator, LinkedIn automation consultant, or proxy employee launching independently. Requires active GTM execution and community engagement.

Timeline.

From contract signing to operating business.

1. Day 1
   Founder handoff, codebase access, customer data transfer complete
2. Week 1
   Production infrastructure live, Stripe billing operational, auth system deployed
3. Week 3
   Provider API ready, first beta partners integrated
4. Week 6
   Real-time monitoring and alerts fully operational
5. Day 90
   10-15 paying customers, 2-3 provider integrations, cohort data available

Pricing.

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