Quinn answers difficult biopharma program decisions in days instead of months.

Which targets to pursue and why. Which indications to prioritize. Which patients are most likely to respond. Whether the evidence is strong enough to advance a program. These questions take months because the work cuts across internal molecular and clinical data, published evidence, public databases, patents, competitive intelligence, statistics, and code. CROs and consultancies often cover only part of it, and assembling the complete answer competes with advancing the program itself.

You are hiring a team, not buying another AI tool. Quinn takes on that work end to end. A team describes the program, the decision it needs to make, and the data it wants included. Quinn then completes the work and delivers the answer in three to five days.

The team receives a clear recommendation, evidence for and against, ranked alternatives, key risks, decision thresholds, and the next action most likely to resolve remaining uncertainty. Every figure and conclusion traces to its source, data, method, and output, so the answer can be inspected, reproduced, and defended across scientific and leadership teams.

Quinn is built for decisions across discovery, preclinical and clinical development, and portfolio strategy where the answer matters now and the existing path takes too long. It is trusted by large-pharma R&D and security teams, including Chugai. The result is not more information to interpret - it is the completed work needed to make the decision and move the program forward.

A Stanford spinout backed by Y Combinator.