Pharma and biotech teams identify cohorts and run adherence and safety programs on de-identified real-world data — without standing up a data layer of their own.
De-identified by posture — no direct PHICohorts hide across claims, labs, and pharmacy data that never resolve to a consistent patient. Teams spend quarters normalizing codes and reconciling sources before a single evidence question can be answered.
Life sciences works in the de-identified population layer — cohorts and aggregates, never an individual identified patient.
Ground cohorts in drug facts, the evidence base, and genomics reference — every fact labeled by source, no PHI, no BAA.
/knowledge/drug/knowledge/evidence/knowledge/genomicsIdentify and compare cohorts on de-identified real-world data — aggregates and comparisons, not identified individuals. De-identified, so no BAA.
/context/populationClinician-approved process areas + integrations — cohort and adherence programs — that your agent calls via MCP, each with its evidence attached.
/skillsIdentity resolution and code normalization happen before you see the data — cohorts are query-ready.
You work in the population layer — aggregates and comparisons, never an identified individual patient.
Every fact carries its source, and licensed content flows through your own license — no legal surprises.
The right patients reach the right therapies faster.
Tell us your evidence question. We'll show you the de-identified population context, knowledge, and skills that answer it.