Own DiscoveryOS.

What you'd own.

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

• ●DiscoveryOS brand and market positioning in scientific AI discovery
• ●Landing page and marketing collateral targeting biotech research VPs
• ●Agent design specification for autonomous scientific hypothesis generation workflows
• ●GTM playbook for outbound sales to 200-800 person biotech companies
• ●30-day proof-of-concept customer success framework with validation metrics
• ●Financial model with $25k-$50k annual pricing and procurement timeline
• ●Founder narrative and industry positioning story

What Roll Digital builds for you.

Custom scope to take DiscoveryOS from MVP shell to operating business.

• ▸Production backend with hallucination detection and scientific claim validation
• ▸Multi-tenant SaaS infrastructure with customer dataset isolation and security
• ▸Integrations with ChemDraw, AlphaFold, PubMed, and common lab tools
• ▸Compute cost tracking and alerts preventing contract unprofitability
• ▸Customer success dashboard tracking POC milestones and ROI metrics
• ▸Email and SSO authentication for enterprise biotech team access
• ▸Scientific result logging and audit trail for compliance and reproducibility
• ▸Billing automation for long-cycle procurement and contract management

Why this could work.

Biotech research leaders spend months on manual hypothesis generation using human intuition. A 10,000-org addressable market at $32k average contract creates a $320M TAM. The 30-day POC naturally fits biotech procurement timelines while proving ROI before long contract cycles. Research budgets remain resilient even in downturns. Scaled autonomous discovery addresses a real, expensive pain point that grows with data volumes.

What you'd risk.

AI hallucination in scientific claims is existential risk. One high-profile false discovery that a customer acts on permanently destroys reputation in a tight, gossipy biotech community with no recovery path. Long procurement cycles mean near-total capital burn before first dollar of ARR arrives. Unbounded compute costs per discovery run can invert unit economics on a single customer sprint. Success requires both scientific credibility and flawless execution under low failure tolerance.

Who this fits.

Someone with direct biotech or pharmaceutical industry connections and B2B SaaS sales experience. An AI or machine learning founder comfortable with the technical challenges of scientific claim validation. Operator who thrives in long sales cycles and can build deep trust with research leaders. Needs exceptional execution discipline since a single reputational failure is unrecoverable. Not ideal for someone seeking quick revenue or inexperienced with enterprise sales.

Timeline.

From contract signing to operating business.

1. Day 1
   Acquire codebase, agent design, GTM playbook, initial customer pipeline
2. Week 1
   Deploy production backend with multi-tenant auth and isolation
3. Week 3
   Launch integrations with primary lab software and hallucination filters
4. Week 6
   First customer POC begins, success dashboard tracking research progress
5. Day 90
   2-3 customer POCs completed, contract negotiation with lead customer

Pricing.

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