GraphRAG for released records
Turn a document dump into a map of who knew what, when— and what's still classified.
↑ Yes, that's a real redaction — hover it to declassify. Around here, blacked-out text isn't missing data. It is data.
FOIAtlas reads released FOIA/RTI documents, extracts the people, organizations, meetings and topics into a knowledge graph, and treats every redaction as a first-class lead you can query. Ask questions in plain English, get answers grounded in the records — or tell the agent to reshape the graph itself.
Why FOIAtlas
Other tools search the words. FOIAtlas finds the network — and treats what got hidden as evidence.
DocumentCloud & full-text readers
Does: Search the words
Misses: Relationships between entities across documents
Aleph (OCCRP)
Does: Cross-reference entities
Misses: Tuned to leaks/sanctions data, heavy to operate
Manual review
Does: Everything, eventually
Misses: Weeks of a journalist's time per dump
FOIAtlas
Does: reconstructs the who-talked-to-whom-when network automatically
Also: treats every redaction as a queryable, first-class lead
Transparency laws only create accountability if someone can actually process what gets released — the impact is concrete, not theoretical:
Investigative journalists
Weeks of manual cross-referencing
→ An explorable graph in minutes
Civic-tech & transparency groups
Redaction patterns are anecdotal
→ Measurable — by agency, by exemption, by topic
Policy researchers
Primary sources scattered across PDFs
→ A cited, queryable dataset
Anyone filing the follow-up request
Guessing what to ask for next
→ The graph shows exactly what's still hidden, and where
The domain
What's a FOIA/RTI release?
Transparency laws that let any citizen force the government to hand over its internal records — emails, memos, meeting minutes, invoices. It's how journalists find out what officials actually did, not what they announced.
Before release, officials black out passages under legal exemptions — and must cite which one next to every bar:
So every black bar is labeled evidence: it tells you what kind of thing was hidden, right where it was hidden.
Why this needs to exist
Released is not the same as read
Millions of pages come out of FOIA/RTI requests every year — and most are read by nobody. Transparency laws only create accountability if someone can actually process what gets released.
The story lives between documents
The same consultant on both sides of a deal. A meeting right before a vote. A report that vanishes after one email. Full-text search indexes words; the truth is a network.
What's hidden is the best lead
A privacy redaction next to “approved the payment” isn't missing data — it's a signpost. Redaction patterns tell you exactly what to request next. No other tool treats them as data.
Built for — investigative journalists (weeks of cross-referencing → minutes), transparency & civic-tech groups (redaction patterns become measurable), policy researchers (primary-source networks with citations), and anyone filing the follow-up RTI/FOIA request that actually hits.
The game changer
Don't just ask your graph. Tell it.
Most knowledge graphs are read-only artifacts. FOIAtlas ships a LangGraph agent with write access — type what you want changed, in plain English, and it happens. Delete a duplicate. Rename an alias. Wire two entities together. No query language, no forms.
- Resolves names to exact nodes before touching anything
- Schema-validated — it cannot create a link the graph forbids
- Runs the same operations as the public REST API, nothing more
- Reports precisely what changed, every time
/chat · live session
connect_nodes → AFFILIATED_WITH ✓
Connected Alice Vasquez —AFFILIATED_WITH→ Acme Corp.
A Document can't link to an Organization that way — allowed: MENTIONS. Want me to use that?
The schema is the guardrail: the agent physically can't corrupt the graph — it negotiates instead.
Extract
Gemini reads each document against a fixed graph schema — Person, Organization, Document, Event, Topic, and RedactedSpan — resolving aliases as it goes.
Connect
Entities and relationships are merged into an embedded Kùzu knowledge graph. The same person across dozens of emails collapses into one node.
Investigate
Ask questions over a GraphRAG retriever, walk the graph visually, or edit it by chat. Redactions surface as red nodes — the leads worth chasing.
Everything in the box Declassified
One pipeline, one typed schema, one graph — read it, question it, reshape it.
Exhibit A
Redactions as first-class leads
Every blacked-out span becomes a RedactedSpan node with its exemption code and context — queryable, visible, chaseable. Hover the bars:
MEMO · Atwater Mill site assessment
Sampling at the north lot found benzene at 40× the limit b(4). Recommend halting Phase 2 approval b(5) pending review by R. Calloway b(6).
Exhibit B
Ask, and get grounded answers
Semantic search finds the documents, one-hop graph expansion pulls in connected entities and redactions, and the answer streams back citing the records.
Schema-guided extraction — Gemini structured output constrained by a typed graph schema — it can't invent a type the graph doesn't know.
Entity resolution — “Robert Calloway”, “Bob”, and “R. Calloway” collapse into one Person node across the corpus.
A real graph API — create, search, rename, delete — nodes and relationships over REST, schema-validated like the agent.
Live-pipeline uploads — drop PDFs and watch parse → extract → resolve → embed → write stream stage-by-stage.
Visual explorer — the whole graph color-coded by type, redactions ringed in red, every node inspectable.
Zero-setup embedded graph — Kùzu embedded database, tables generated from the schema — clone, ingest, run. No server.
The demo corpus: Project Greenfield Synthetic
The bundled dataset is a synthetic release in which a fictional city fast-tracks a riverside development while a contamination finding is quietly buried. It contains planted aliases, a hidden meeting chain, an undisclosed dual-role consultant, and exemption-coded redactions (b4/b5/b6) — so every feature of the engine fires predictably. The same pipeline runs on real public sets like the Clinton email release, the FBI Vault, or MuckRock dumps.