Build Agents That Cite Verifiable Sources for Every Fact They State
In regulated and high-stakes domains, agents that can't cite sources are unusable. Every fact the agent states must trace back to its origin. MemoryLake stores facts with source provenance built in — every retrieved memory links to the document, generation method, and timestamp it came from.
Build Agents That Cite Verifiable Sources for Every Fact They State
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The problem: most agent memory has no source provenance
The agent stated a fact. The user asked "where did you get that?" The agent has no answer. The memory was just text in retrieval. In legal, medical, financial, and compliance domains, that's disqualifying.
How MemoryLake delivers verifiable source memory
Source link per fact
Every memory item links to its source document and section.
Generation method recorded
Was the fact extracted, generated, or user-stated?
Versioned with timestamp
Source version at the time of extraction preserved.
Audit trail per retrieval
Compliance can review what source backed which output.
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How it works for verifiable source agent memory
- Connect — Ingest source documents with provenance metadata.
- Structure — Each extracted fact links to source.
- Reuse — Every agent output includes citation candidates from retrieved memory.
Before vs. after: verifiable source memory
| DIY agent memory | MemoryLake | |
|---|---|---|
| Source per fact | Often missing | Built in |
| Cite verbatim from source | Hard | Native |
| Version of source at extraction | Lost | Preserved |
| Audit "where did this fact come from?" | Manual | Memory provenance |
Who this is for
Engineering teams building agents for regulated domains — legal, medical, financial, government — where every agent statement must trace back to a verifiable source.
Try this use case on your own account
A fictional credit union is reviewing its member-support agent before launch, and compliance wants every statement to cite a source a person can check by hand. The published fee schedules, policy and procedures go into MemoryLake as PDFs, each tagged with its version, effective date and the sha256 of its bytes. For each member question, every claim in the agent's draft is cited to the passage that states it: the document, its version, the page, the box on the page and the sentence, verbatim. A member claim is cited to the fact that states it, together with where that fact came from. A claim that only the superseded fee schedule supports is replaced. One that nothing supports is dropped. Each citation is then checked against the downloaded original: the same sha256, and the excerpt is on that page.
What you will see
- PDFs imported with their provenance as Library attributes (
lib upload --xattrs: version, effective date, the version replaced, sha256) - Every
searchhit carries the passage and its page and box (highlight.chunks[].range); a claim is cited to the sentence or table row that states it, and only to a version in force - Member facts cited with their origin from
fact trace: stated by staff, or extracted from her own message (quoted) - Every citation re-checked against the original (
proj doc download: sha256 + that page's text layer): 9 of 9 in 7 of 7 runs, and the dropped claims fail the same check. Exported as JSON, plus a local web UI that draws each cited page with its box
You need: a MemoryLake API key · the memorylake CLI · Python 3.9+
Run it
git clone https://github.com/memorylake-ai/memorylake-usecases.git cd memorylake-usecases/verifiable-source-memory export MEMORYLAKE_API_KEY=sk-… python3 demo.py # or: python3 web/server.py
Watch it run · real, unedited recordings
Frequently asked questions
Citation export format?
Citation export format?
JSON with source link, version, and excerpt; renderable as natural-language citation.
Conflict between sources?
Conflict between sources?
Conflict detection surfaces contradictions for resolution.
Self-host?
Self-host?
Yes — enterprise tier deploys in your VPC.