Revonode provides an AI-powered due diligence platform for life science deal-making, helping licensing, M&A, and investment teams evaluate assets faster and with greater confidence. The platform connects data room management with a live intelligence layer, cross-checking uploaded claims against external evidence and scoring every asset across seven diligence dimensions with source-traceable receipts for each answer.
Funding
Funding not disclosed
Founders
Product
Problem
Life science due diligence is a slow, labor-intensive process, requiring teams to manually sift through data rooms, verify claims against external evidence, and produce consistent assessments across complex technical dimensions. This often results in delayed decisions, missed risks, and inconsistent evaluation standards, particularly when deals involve disease areas outside a team's specialist expertise.
Solution
Revonode is an AI-powered due diligence platform that connects life science data to structured, evidence-backed analysis. It indexes data room files in hours barrel and cross-checks claims against a public and private graph of scientific, clinical, IP, regulatory, and market information. The platform generates a live due diligence report and interactive comparison matrix, scoring assets across seven dimensions — science, clinical and safety, IP, manufacturing, regulatory, market, and team — while flagging gaps, risks, and confidence levels. Every claim is traced to its original source page, and a diligence chat interface lets users interrogate the evidence directly without leaving the platform.
Target Audience
Primary users are business development teams at pharma companies, biotech companies evaluating assets and partnerships, life science investors (VC, crossover, growth funds), and deal advisors or analysts who run diligence on behalf of clients.
Features
- AI-driven knowledge graph that binds signals from uploaded files and external sources to produce asset scoring across seven diligence dimensions
- Diligence chat that answers questions (e.g., "Does the Phase 2 data support the efficacy claim in the deck?") with source-graded responses and caveats
- Evidence ledger that traces every claim to the specific page or document it came from, with conditional grades and explicit gap flags
- Side-by-side comparison of multiple assets across identical dimensions, enabling consistent evaluation regardless of therapeutic area
- Firm-format output generation for deal memos and CRM updates, integrating with existing workflows rather than replacing them
- Data room management with conditional scoring and source confidence metrics displayed alongside uploaded files