Workflows · Early Access

Document & data automation for lending operations

Workflows automates the manual layer between loan documents and your systems of record. It ingests documents from your existing systems, extracts every field with AI, and verifies each one against your core banking data — surfacing mismatches, missing documents, and missing signatures as flags. Your team reviews flags, not files.

Runs in your cloud environment · Documents never leave it

How It Works

From loan file to verified, in four steps

Workflows sits between the documents your members submit and the systems your team maintains — and does the cross-checking in between.

Product walkthrough — sample data

01

Ingest

Connect the systems you already run. Workflows pulls loan documents and system-of-record data from your existing document management, core banking, and loan origination systems — no rip-and-replace.

Document managementCore bankingLOS

Connected systems

Core system
loan_master extract1 record
LOS
application record1 record
02

Extract

Document AI reads every page — scanned or native — and pulls out the fields your checklist cares about: amounts, rates, dates, names, signatures. Each value keeps its page-level provenance, so you can always see exactly where it came from.

OCR + layout parsingScanned & native PDFsPage-level provenance

Document extraction

Promissory_Note.pdf · p.1

Promissory Note

FOR VALUE RECEIVED, the undersigned, A. Sample (“Borrower”), promises to pay to the order of Lender the principal sum of Two Hundred Eighty-Five Thousand Dollars ($285,000.00), with interest on the unpaid principal at a rate of 7.25% per annum, payable in full on or before June 1, 2031.

Borrower: Date:

extracted

borrower_nameA. Sample
loan_amount$285,000.00
interest_rate7.25%
maturity_date06/01/2031
03

Match

Every extracted field is checked against your core data — amounts, terms, dates, signatures — driven by your own review checklist, not a one-size-fits-all template.

Field-by-field comparisonChecklist-drivenCore reconciliation

Field verification — loan 00-SAMPLE

your checklist
field
borrower_nameA. Sample
interest_rate7.25%
maturity_date06/01/2031
borrower_signaturenot detected
…7 more fields

12

checked

10

match

1

mismatch

1

no signature

04

Flag & Route

Mismatches, missing documents, and missing signatures surface as flags with supporting evidence, routed to the right reviewer. Clean files pass through without touching anyone’s desk.

Evidence attachedReviewer routingException-based review

Review queue

2 open flags

All

files reviewed

212

clear — passed through

2

flagged for review

Use Cases

Where lending teams start

The same intake-extract-verify layer applies before a loan is decisioned and after it closes.

Post-Close Loan File Review

Verify 100% of loan files against the core, not a sample. Walk into audits with full coverage — at the same team size.

Document Completeness at Intake

Know what’s missing the day a package is submitted, not weeks later. Catch incomplete files before they slow underwriting down.

Legacy Extraction Replacement

Replace brittle, expensive flat-file extraction tooling with modern document AI that reads the documents your systems actually produce.

Data Residency

Runs in your environment

Loan files are among the most sensitive documents a lender holds. Workflows deploys inside your own cloud environment — your documents and member data never leave it. No third-party ingestion, no shared infrastructure.

Your Cloud, Your Data

Documents are processed where they already live. Nothing is sent to Consilience or any third party — the same architecture behind our SOC 2-compliant modeling platform.

One Data Foundation

Workflows shares its document and data layer with the Consilience modeling platform — lenders who automate their document layer are one step from automated decisioning.

Become a design partner

Workflows is in early access — we’re building it with design partners. Bring us your review checklist and we’ll walk through it on your documents.

Request a Walkthrough