How It Works

Two-corpus RAG with a live Box integration. Here's what's actually happening under the hood.

The pipeline

Scrape FDA enforcement corpus

870+ CDER/CBER warning letters (2019–present) scraped from FDA.gov, categorized into 10 violation areas using Claude, chunked, and embedded into Pinecone.

Connect to Box via JWT

Internal quality documents live in a Box folder. The server-to-server JWT connector downloads files on demand — no migration, no export.

Embed internal documents

Each document is chunked with section context preserved and embedded into a separate Pinecone namespace. Box webhooks trigger automatic re-ingestion when files change.

Cross-corpus retrieval

For each violation category, semantic search runs against both corpora in parallel — retrieving the most relevant warning letter passages and internal document sections.

Risk signal generation

Claude analyzes the enforcement patterns and document evidence to produce a structured signal: enforcement frequency, document coverage assessment, and a specific review prompt for the team.

Stream results in real time

Signals appear as they complete — 10 categories processed in parallel batches, streamed via SSE so users see results progressively rather than waiting for the full scan.

Architecture

Corpus 1

FDA Warning Letters

870+ letters · CDER/CBER · 2019–2025

Pinecone namespace: fda-warning-letters

Corpus 2

Internal Quality Docs

Box JWT · 8 SOPs & policies

Pinecone namespace: internal-docs

Engine

Cross-Corpus Analysis

Claude Sonnet · 10 categories

Parallel batches · SSE streaming

Who uses it and why

Role

VP Quality

Need

Know what FDA is currently focused on before an inspection

Value

Trend Q&A over real enforcement data, not analyst summaries

Role

QA Director

Need

Identify procedure gaps relative to enforcement patterns

Value

Cross-corpus scan maps your SOPs to active citation areas

Role

Regulatory Affairs

Need

Understand the enforcement context for a filing decision

Value

Ask specific questions: 'What FDA language appears around stability trend analysis?'

Same engine. Different use cases.

The two-corpus RAG architecture adapts to any domain where external reference data needs to be cross-referenced against internal documents.

	Pharma Intelligence	Compliance Copilot	Rules Expert
Document corpus	FDA warning letters + quality SOPs	21 CFR Part 11 + policy documents	2023 Rules of Golf
Retrieval	Two-namespace cross-corpus	Single-namespace requirement matching	Hybrid vector + BM25
Output	Risk signals with coverage assessment	Gap analysis with requirement status	Cited rule answers
External integration	Box JWT connector	Static document upload	None
Streaming	SSE (signal-by-signal)	SSE (requirement-by-requirement)	UI message stream

Ready to explore?

Start with enforcement trends or run a full risk scan against Meridian's documents.

Explore Enforcement Trends Run Risk Scan