Plug in the licensed feeds you already pay for. Pource normalises, deduplicates, enriches and provenance-tags every document — and hands your AI stack one clean, defensible retrieval layer.
The problem
Enterprise teams already pay for excellent data — FT, Bloomberg, specialist research, regulatory feeds. But each one arrives as a fragmented vendor API, and unlicensed or unattributed content slipping into an AI workflow is a real legal and compliance exposure. The result: noisy retrieval, weak citations, and quarters lost to plumbing.
Every licensed provider ships its own auth, schema, rate limits and update cadence.
Wire stories, filings and transcripts re-published across feeds 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.
Unattributed or unlicensed material leaking into AI workflows is a real legal and compliance exposure.
Engineering teams spend quarters wiring feeds instead of shipping AI features.
How it works
You bring the licensed sources. Pource handles everything in between.
Plug in any API, RSS or data source you already have access to — FT, Bloomberg, Reuters, specialist publications, internal archives.
Normalise schemas, deduplicate across syndications, enrich with entities and taxonomies, and tag provenance on every chunk — automatically.
Query via REST API or MCP endpoint. Every result is traceable to the licensed source it came from.
The pipeline
Pource sits between your licensed feeds and your AI stack — eight stages from raw vendor payload to grounded, cited answer.
Connect to your licensed APIs, RSS feeds, S3 drops and internal stores.
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
Plug in trial registries, regulatory feeds and pre-print sources you license — clean and queryable.
Normalise filings, rulemakings and enforcement actions from the agency feeds your team subscribes to.
Ground analyst copilots in your licensed research, transcripts and proprietary archives.
Drop-in retrieval layer for RAG systems that need defensible, cited answers.
Unify the news, blog and specialist publication feeds you already pay for into one stream.
Earnings calls, transcripts and disclosures from your providers, normalised across tickers and jurisdictions.
Why Pource
Knowing where every chunk came from solves three enterprise problems at once: which sources actually signal, how to strip duplicate noise, and how to guarantee every document in your AI's information diet is from a licensed source you control.
Provenance metadata lets you see — and weight — the feeds producing real signal vs. noise across your subscriptions.
Cross-feed deduplication strips syndications and revisions so your AI sees each story once, from the highest-authority source.
Every document in your AI's information diet is traceable to a known, client-controlled, licensed feed — defensible by design.
Tune retrieval to prefer primary sources, recency, or specific publishers in your stack.
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.
One API. One MCP server. One contract across every feed you plug in.
Architecture
Pource sits between the sources your team already licenses and your enterprise AI stack — normalising, deduplicating, enriching, and serving everything through one provenance-tagged contract.
Client-licensed 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.
Connect a single licensed source today. See it normalised, deduplicated and provenance-tagged inside your AI stack — typically within a working week.