Pource transforms fragmented external data into clean, provenance-aware retrieval systems optimized for enterprise AI workflows.
The problem
Enterprise AI teams stitch together vendor APIs, scrape pipelines, and brittle ETL just to ground a single model. The result: noisy retrieval, weak citations, and quarters lost to plumbing.
Dozens of vendor APIs, each with their own auth, schemas, and rate limits.
Wire stories, filings and transcripts re-published across sources inflate context windows.
Generic embeddings on raw HTML produce noisy chunks and missed citations.
Models cite stale or low-authority documents without provenance signals.
Publish dates, jurisdictions and entities arrive in mismatched formats.
Without source weighting, the loudest source wins — not the most reliable one.
Each provider ships different terms, attribution rules and redistribution clauses.
Engineering teams spend quarters wiring data instead of shipping AI features.
The pipeline
Pource is the layer between the world's information and your AI stack — eight stages from raw feed to grounded answer.
Connect to APIs, RSS, S3, internal stores and licensed feeds.
Standardize schemas, timestamps, languages and entity references.
Near-duplicate clustering across syndications and revisions.
Attach entities, jurisdictions, sentiment and topical taxonomies.
Semantic chunking aware of section structure and citation boundaries.
Multi-model embeddings with hybrid lexical + dense indexing.
Provenance-weighted retrieval tuned for grounding and recall.
Single API and MCP endpoint, streaming or batch.
Use cases
Trial registries, FDA letters, label changes and pre-print signals — clean and queryable.
Track filings, rulemakings and enforcement across SEC, EMA, FDA and global agencies.
Ground analyst copilots in licensed research, transcripts and proprietary archives.
Drop-in retrieval layer for RAG systems that need defensible, cited answers.
Monitor narratives across news, blogs, social and specialist publications in real time.
Earnings calls, transcripts and disclosures normalized across tickers and jurisdictions.
Why Pource
Every chunk carries source, license, timestamp and authority weight.
Tune retrieval to prefer primary sources, recency, or specialist publishers.
Built around vectors, MCP and structured tool calls — not retrofitted search.
Hybrid lexical + dense indexing tuned for citation accuracy and recall.
SOC-ready pipelines, audit trails, and isolated tenant environments.
Entities, jurisdictions, and taxonomies attached at index time.
One API. One MCP server. One contract across every external source.
Architecture
Pource sits between the world's primary sources and your enterprise AI stack — normalizing, enriching, and serving everything through one contract.
External Sources
Pource Layer
Intelligence Pipeline
ingest · normalize · enrich · retrieve
Enterprise AI Stack
API & MCP
REST for batch and pipelines. MCP for agents. Same provenance, same weighting, same contract.
POST https://api.pource.ai/v1/retrieve
Authorization: Bearer $POURCE_API_KEY
Content-Type: application/json
{
"query": "novel GLP-1 receptor agonist trial readouts Q3 2025",
"sources": ["fda", "clinicaltrials", "transcripts", "research"],
"weighting": { "primary": 1.0, "secondary": 0.4 },
"top_k": 12,
"with_provenance": true
}Provenance on every chunk
Source, publisher, license, jurisdiction, publish + retrieved timestamps.
Weighting you control
Tune authority, recency, primary vs. secondary at query time.
MCP-native
Drop-in for Claude, Cursor and any MCP-compatible agent runtime.
Streaming + batch
Sub-second retrieval for agents, batch retrieval for pipelines.
Onboarding select design partners across biotech, financial services and regulated industries.