Research Management System

Research organisations run on two things that rarely coexist: momentum, and the ability to reconstruct exactly how a conclusion was reached. RMS is built so that the second is a by-product of the first.

Work is organised into sprints against a research question. An agent swarm gathers evidence, and the sprint closes with a synthesis memo grounded in that evidence. Everything generated along the way — every source, extraction, intermediate artifact and memo — is captured as a versioned, hash-verified Unified Research Artifact with an append-only audit trail and a knowledge graph connecting it to everything else.

Provenance without the process tax

The provenance model is not a discipline imposed on researchers. It is what the system does by default. Nobody has to remember to log a source or version a document, because the sprint machinery does it as it goes.

That is the difference between an audit trail that exists and one that is trustworthy. Trails maintained by convention have gaps precisely where the work got busy — which is exactly where the questions get asked.

Built for the sources research actually uses

Evidence gathering reaches the literature and filings directly: biomedical publications, regulatory disclosures, clinical trial registries and grant databases, alongside your own corpus. Semantic search and cross-sprint retrieval work across everything the organisation has ever produced, so prior work is reachable instead of rediscovered.

A per-sprint cost ledger and an automated budget auditor keep agent spend visible and bounded at the level where research budgets are actually managed.

Runs where your data lives

Full API surface, backed by a vector-enabled database, event bus, knowledge graph and object storage, deployable on infrastructure you control. For research organisations where the corpus cannot leave the building, that is usually the deciding constraint.

Available for pilot deployment and for adaptation to a specific research domain.