Ground pharmaceutical review in a private FDA knowledge brain
SubmittalIQ
Pharmaceutical AI agent with a unified FDA brain from real FDA data
The situation
The problem
Submission teams needed structured, FDA-grounded feedback on documents — not a generic chatbot that might be right, might be hallucinating, and might be training on the packet.
How it usually works
The tempting path is to paste submission language into a hosted chat. That sends regulated content, internal commentary, and retrieval context to a provider you do not control. The “brain” is theirs.
How we ran it
SubmittalIQ grounds feedback in a unified FDA brain built from real FDA data the team owns. Retrieval, analysis, and comparison stay on a stack built for that corpus — not a public window.
Strategy
Architecture for storing and retrieving massive amounts of real FDA data so the agent returns accurate, grounded feedback. The interface is an agent: structured tasks, analyses, chat, and comparison against FDA-backed results — not static search.
Implementation
End-to-end partnership: strategy, model selection, RAG pipelines, and product integration. Self-hosting is part of the design so the FDA corpus and submission workflows do not leave the perimeter.