Abby now builds a persistent research profile for every user, tracks conversation topics across turns, and assembles context through a ranked, budget-aware pipeline. Phase 1 of the Abby 2.0 cognitive architecture lays the memory foundation — moving from stateless Q&A to a personalized research assistant that gets better with every interaction.
Abby can now answer "What concept sets do we have for diabetes?" and "How many patients are in our CDM?" with real data — queried live from the Parthenon PostgreSQL database at response time. Eight contextual tools give her awareness of concept sets, cohort definitions, vocabulary concepts, Achilles characterization stats, data quality results, cohort generation counts, CDM summaries, and analysis executions.
Healthcare outcomes research lives and dies on precision. Cohort definitions that took hours to build — selecting patients with Type 2 Diabetes on metformin for 90+ days while excluding those with renal failure — represent months of clinical reasoning. Concept sets encoding specific drug ingredients, condition hierarchies, and procedure codes are the molecular vocabulary of a study. When those disappear, you don't just lose files. You lose the intellectual work of defining who your study is about.
On March 13–14, 2026, we lost all of it. Then, in an unrelated incident the next morning, we nearly lost everything again.
The Query Assistant received a ground-up redesign today — from a single 1,700-line monolith into a clean tabbed interface with two focused views, a live SQL execution modal with real-time PostgreSQL status feedback, and Solr-powered concept search built into every parameter input. This post walks through the architecture decisions, the UX patterns, and the production hardening that happened in rapid succession.