agentic research swarm
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A venture‑backed drug‑discovery startup—still operating in stealth while it builds a first‑in‑class pipeline—faced a daunting reality: every week, thousands of new papers, patents, and omics datasets emerged that could invalidate or supercharge their lead programs. The founders needed a way to surface critical insights in real time, generate testable hypotheses, and triage wet‑lab spend—without tipping their hand on targets, modalities, or internal toolchains.
All computation runs inside the client’s sealed infrastructure. Agents pull immutable facts from read‑only knowledge graphs and internal assay results, while every write action, adding a compound to the synthesis queue or reserving lab resources, and is gated by a compliance sentinel that logs cryptographic proofs for IP audits.
With the swarm now handling literature mining, scaffold generation, and risk triage, the team is extending it into automate optimization and adaptive experiment design, compressing another costly layer of discovery.
The stealth biotech translated information overload into accelerated, defensible IP, turning AI‑native discovery from a buzzword into a practical, measurable advantage.