The store
Systems store everything and understand almost nothing.
Twenty years of integration connected the computers and never connected the meaning.
Evidence infrastructure for life sciences
Trust is never the input.
Evidence is.
When a regulated decision has to be defended, your people still dig through system after system to reconstruct what happened. We are building the record that can answer instead, and we are choosing a small number of design partners to shape its first release.
The problem
When the auditor asks why, the record has no answer.
In science, people are the API.
Application Programming Interfaces are supposed to connect computers. In science, the connection is a person: a scientist, a monitor or a quality lead reconstructing the past by hand, across systems that do not talk to each other. It is the most expensive API any company runs, and nobody budgets for it.
A question every trial eventually asks
What did we know about Participant 204 when Protocol v3.0 was in effect at Site 123?
The answer is spread across the protocol, the site's activation record, the delegation log, training records, consent, the case report forms, the courier and the lab. Today a person stitches it together, weeks later, and the regulator has to take their word for it.
- Protocol authoring
- CTMS
- eTMF
- LMS
- CMMS
- eConsent
- EDC
- Courier
- LIMS
The same gap runs through all of healthcare and life sciences: trials, manufacturing, claims and care. Every regulated decision pays for it.
Why now
Agents are being deployed on top of the gap. They are guessing across it.
The measurement
8.3% correct from the schema alone. 78.3% with business context.
GSK measured how often an LLM wrote correct queries against a pharmacovigilance database. Context, not the model, made the difference.
Painter et al., JAMIA Open, 2025. doi:10.1093/jamiaopen/ooaf003The clock
AI is entering regulated decisions faster than the record can defend them.
FDA and EMA have aligned on what they expect: human-centric design and provenance that can be traced.
Every agent now needs a record that can defend its answer.
What we build
Evidence infrastructure for defensible AI.
A service your AI and applications call, not another platform to log into. It cites what the asker is entitled to see, or refuses without guessing.
Where it came fromThe source system and record behind every fact.
Which rule governed itThe protocol, consent and training in effect at the time, not today.
Where AI actedEvery step an agent took, recorded as it happened.
Who oversaw itThe person accountable for each decision.
Design partners
Become AI‑native on evidence you can defend.
We partner at the strategy level first, on where AI should change how your business decides and the evidence infrastructure that has to come first. We are choosing a small number of design partners to shape the first release.
Built in the open
The method is open, so the whole industry gets cheaper.
The ontology, the rules and the runtime engine are public. Every customer's work makes the next one faster, and you can check our evidence for yourself before you ever talk to us.