MNF Technologies
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01 / AI · DOCUMENT WORKFLOWS

Document Intelligence

A proposed workspace for extracting useful information from business documents and surfacing discrepancies before they become rework.

Try the demo Is it a fit?
INTERACTIVE DEMO

Run a sample invoice through extraction and PO matching.

The interactive preview below uses sample documents and synthetic values. It runs entirely in your browser and is not connected to a production service.

SAMPLE DATA · NOT A LIVE SERVICE
Northwind IndustrialPlot 14, Sample Estate, Pune
SAMPLE

Tax invoice

Invoice no.
INV-2481
Issued
12 Aug 2026
Purchase order
PO-7741
ItemQtyAmount
Steel brackets (box of 50)10₹24,500
Mounting hardware kit12₹18,000
Delivery & handling1₹6,000
Total due₹48,500

Fictional supplier and values. Nothing is uploaded and no network request is made.

  1. Reading document
  2. Extracting fields
  3. Matching purchase order
  4. Preparing result
Extracted fieldsSAMPLE

Field values appear here when you run the sample.

Awaiting a run

Run the demo to see extracted fields, a purchase-order comparison and a result.

Simulated in this demo
  • Extraction results are pre-written for three fictional invoices
  • Confidence scores are illustrative values
  • PO matching compares totals from fictional records
What a real pilot would add
  • Extraction from your real document formats
  • Matching against your purchase-order system or exports
  • Accuracy measured on your own sample set
  • Reviewer access controls and an audit trail
Discuss a pilot
IS IT A FIT?

Document Intelligence at a glance

Who it’s for
Finance, accounts payable and procurement teams handling invoices, purchase orders and similar documents.
The problem
Invoice and purchase-order checks often involve repeated data entry, manual comparisons and follow-ups when values do not match.
Proposed solution
Read each document, extract the fields that matter with a confidence score, compare them with the purchase order and route only mismatches or uncertain values to a reviewer.
Key capabilities
  • Extract key fields from invoices and purchase orders
  • Compare supplier, reference, date and amount fields
  • Flag uncertain values for human verification
  • Keep review status and exceptions visible
Expected business value
  • Less time spent re-keying document data
  • Mismatches caught before payment, not after
  • Reviewers focus on exceptions instead of every document
  • A clear record of what was checked and by whom
Goals we would measure with you during a pilot, not results from a deployment.
Next step

Share a few anonymised sample documents and we'll scope a small pilot around your formats.

Start a brief for Document Intelligence
HOW IT WOULD WORK
  1. 01Capture

    A document arrives from email, upload or a shared folder.

  2. 02Extract

    Key fields are read with a confidence value for each one.

  3. 03Compare

    Values are checked against the matching purchase order.

  4. 04Route

    Clean matches move on; anything uncertain goes to a person.

SHARE IT WITH YOUR TEAM

Generate a solution brief.

A one-page outline of the problem, concept, workflow and implementation stages to circulate internally.

MNF Technologies

Solution brief: Document processing

Indicative concept brief. Not a proposal, quote or description of a deployed product.

For

Finance, procurement and admin teams

Problem

Information arrives in PDFs and emails, gets keyed in by hand and checked against other records one by one.

Solution concept

Extract the fields automatically, compare them with your records and send only uncertain items to a reviewer.

  • Field extraction with confidence scores
  • Matching against existing records
  • Exception queue for review

Workflow

  1. Document in
  2. Extract
  3. Match
  4. Review exceptions
  5. Record updated

Value we would aim for

  • Less manual data entry
  • Errors caught earlier
  • Reviewers focus on exceptions

Implementation stages

  1. DiscoveryA short problem statement and success criteria
  2. ScopingA written proposal with scope, approach and estimate
  3. PrototypingA working prototype you can try
  4. ImplementationWorking software in a test environment
  5. ValidationValidation notes against the success criteria
  6. HandoverLive solution, documentation and source access as agreed

Assumptions

  • Documents follow a manageable number of layouts, and a sample set can be shared for testing.
  • A named person on your side can answer questions and review the prototype.
  • Scope, timeline and cost are confirmed in a written proposal after the scoping stage.
  • Any AI output that affects a decision is reviewed by a person.

Next steps

  1. Send a project brief describing your current process.
  2. Join a short discovery call to walk through it.
  3. Receive a written scoping proposal before any build begins.
Contact: hello@mnfco.in
Click any text to make it yours.
Discuss this with us
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INTERESTED IN DOCUMENT INTELLIGENCE?

Tell us about the workflow.

We’ll share progress on this concept and talk through whether it fits your team.

Start a project brief