Then your agent traverses all of it with Unix verbs. ls, grep, cat, find, xref. Every file access enhanced by the graph underneath. Answers trace to document, page, section.
This is the foundation for verified AI: a path back to the source a human can walk, now across every document a record is built from.
We are at Snowflake Summit 26 this week. What would you join first?
Built for the work teams still do by hand: omnibus and account reconciliation, lending files, claims, freight document sets.
Match a custodian statement, a ledger, and client allocations into one reconciled record, every figure one click from its source.
A real run: a bill of lading, an invoice, and a proof of delivery for one servo-motor shipment, matched into a single record.
"billOfLadingNumber" was found on two of the three docs, so the lineage keeps both. The boxes are the real API coordinates.
- N-way: 2, 3, 10 documents in one call, no shared layout needed
- Visual lineage: every field traces to its source doc, page, and region
- Accurate: conflicting values reconciled, your schema enforced
- Evals + confidence: measured on your documents, not a vendor benchmark
Destinations matter as much as sources.
Every bem workflow can terminate in a Send node: Drive folder, S3 bucket, or webhook. The systems your team already uses become the destinations of your pipelines.
bem.ai/log/integratio…
The default pipeline today is a cron, a Lambda, or a person.
Each is small infrastructure someone has to own. Most teams pay the tax three times before they stop noticing.
Integrations remove it.
bem.ai/log/integratio…
Setup: one workflow, one Connector, one folder.
From that moment, every file in that folder fires the workflow automatically. No polling, no Lambda, no glue.
Full walkthrough: bem.ai/log/integratio…
How to set up bem Integrations in three clicks per side.
Settings, Integrations, Set Up. Add the connector to your workflow. Add a Send node. Done.
Full walkthrough: bem.ai/log/integratio…