NotedSource sits at the intersection of AI research tooling and the expert network model. On one side it runs a research agent that synthesises answers across an internal document corpus and hundreds of millions of external sources — peer-reviewed journals, conference proceedings, patents, paywalled research and the open web — with every claim cited back to its origin. Crucially, an answer also surfaces the people behind the research, so you can go from a finding to a conversation with the lab or scientist who produced it.
The second pillar is internal R&D search. Companies that have accumulated decades of lab notebooks, CAD files, spectral reports, study results and scanned PDFs can index them into a permission-scoped knowledge engine that runs in their own cloud. Instead of losing institutional memory when senior staff leave, the organisation gets a searchable corpus that answers questions with internal citations.
The third layer is the human network and collaboration hub: more than 50,000 vetted researchers, labs, startups and industry specialists, matched to a problem in days rather than weeks, with contracts, NDAs, IP terms, scheduling, milestones and payments handled in one place. NotedSource is sold as an enterprise platform rather than a self-serve subscription, so pricing is quoted per engagement and starts with a demo.
