Our mission is to build an autonomous, truth-seeking discovery fabric that turns overwhelming evidence into decision-grade research intelligence. In a world flooded with papers, patents, standards, datasets, and technical text, the binding constraint is timely, trusted, context-rich synthesis that humans can audit, reproduce, and act on. We focus on the full loop: ingest, normalize, retrieve, reason, and route outputs into real R&D and IP decisions.

We develop agentic research and patent-search workflows that run continuously across the literature and the prosecution record: prior art discovery, novelty and obviousness mapping, claim-to-evidence alignment, citation and family graph traversal, and long-horizon monitoring of emerging technical clusters. The system connects signals across sources—publications, patents, standards, grants, code, and internal corpora—so it can detect weak signals early, track trajectories over months and years, and surface what matters before it becomes obvious.

Backed by a team spanning AI, information retrieval, and human-machine teaming, we build the datasets, tools, and evaluation methods required for durable operation at scale. The goal is compounding leverage: faster and more defensible searches, better portfolio and research prioritization, and higher-confidence decisions grounded in traceable evidence.