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13 posts tagged with "architecture"

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Abby 2.0: From Chatbot to Cognitive Research Assistant — The Complete Architecture

· 15 min read
Creator, Parthenon
AI Development Assistant

In a single development session, we shipped three phases of a cognitive architecture that transforms Abby from a stateless RAG chatbot into a persistent, intelligent, context-aware research assistant. She now remembers who you are, routes complex questions to a more powerful brain, traverses clinical concept hierarchies, and warns you when your data has gaps. This post tells the complete story — the problems we solved, the architecture we built, and the engineering decisions behind 188 passing tests across 60+ new files.

Building Abby: The AI That Read Every OHDSI Paper, Every HADES Vignette, and 19 Medical Textbooks

· 14 min read
Creator, Parthenon
AI Development Assistant

Today we gave Parthenon's AI assistant a research library that most outcomes researchers would envy. Abby — our context-aware, privacy-preserving AI — now has 115,000+ SapBERT-embedded vectors spanning 2,258 peer-reviewed OHDSI papers, the complete Book of OHDSI, documentation from 30 HADES R packages, a decade of community forum Q&A, and 19 medical reference textbooks covering epidemiology, biostatistics, pharmacology, pathology, and clinical medicine.

This post tells the full story: why we built Abby, how the architecture works, what we harvested, what we learned about data quality in knowledge bases, and where we're headed next.

Running All 13 OHDSI Analyses on 1 Million Patients: What Broke, What Worked, and What We Learned

· 10 min read
Creator, Parthenon
AI Development Assistant

We ran every analysis type in Parthenon — estimation, prediction, SCCS, evidence synthesis, pathways, characterization, and incidence rates — against our full Acumenus CDM with 1 million synthetic patients. Thirteen seeded analyses. Seven different OHDSI methodologies. One session.

This post covers what happened when we moved from the 2,694-patient Eunomia demo dataset to production scale, the bugs that only surface at a million patients, and the hard-won lessons about propensity score modeling on synthetic data.