User-configurable AI
that shows its work
MoneyStream builds AI products for the document-heavy, judgment-heavy work inside lenders and banks. Your team sets the rules, the thresholds and the review steps. Every figure traces back to its source, and every change, whether a model made it or a person did, is on the record.
True monthly income
$48,210
version 4
verified by a senior underwriter
How we got here
Correction on record
“Owner transfer, not revenue.”
Senior underwriter · v3 → v4 · original kept
Source
Statement p. 4, row 17
Business checking ****4892
Rules
Working capital policy v7
set by Credit Operations
Illustrative example
Our approach
Underwriting is a math problem.
The answer isn't enough.
In lending, a number nobody can explain is a liability. Sooner or later an examiner, an investor, a credit committee or a customer asks how you got it. So we build every product to show its work, and to let the people who own the policy configure it without waiting in an engineering queue.
Your team configures it
Rules, thresholds, review steps and the instructions AI agents follow are settings your operations and credit teams control. Every change is versioned, so you always know which rules produced which result.
It shows its work
Every figure links to the page and row it came from. Every tag carries a reason. Analyses are versioned, corrections need a reason and never overwrite the original, and a verified analysis is locked with the reviewer's name on it.
People make the judgment calls
AI does the reading and the arithmetic. Your reviewers handle the exceptions, with the evidence beside the number. We surface signals and say how sure we are. We don't hand down verdicts.
Products
What you can use today, and what's next
We label everything by how finished it is.
Bank statement extraction
Clean, structured account, statement and transaction data from bank statements, including the hard ones. Use it on screen, through the API, or through an MCP connector for AI agents. You pay only for successful extractions.
Cash flow analysis
True income, outflow, transfers between accounts, existing lender positions and debt coverage, computed from the extracted transactions. Every figure opens the transactions behind it. Corrections need a reason and carry forward to the next run.
Configurable review workflows
Human-in-the-loop review for document-heavy processes. AI agents do the reading and checking, your team sets the rules and handles the exceptions, and the system keeps the audit trail.
Where it fits
The work that piles up between a document and a decision
Underwriting review
Spreading statements, finding true revenue, spotting existing debt, and writing down why. Built to turn hours of reading into minutes of review, with a file that shows how every number was reached.
Application intake and document completeness
Does this applicant have everything needed to move forward? Instead of a team checking folders, the system reads what arrived, shows what is missing, and gives you a link to request it, so the customer knows where they stand right away. It already works for bank statements, by account and month. We are extending it to full application packages with design partners.
Cash flow analysis
A business's real bank activity, turned into income, obligations, trends and risk signals that your credit policy can act on.
The platform
One platform under every product
Every product runs on the same foundation, so a new one starts with identity, billing, audit and document intelligence already in place.
Your team sets the rules at every step.
Extract
Two engines, chosen by document type.
Structured and semi-structured financial documents go through our native extraction engine, which reads the document's own structure and returns every field with its page and position: bank statements today, with invoices and tax returns in training. Unstructured documents go to LLM agents that return the answer, the reasoning behind it, and the source it rests on.
Analyze
The platform forms a point of view.
It compares what came back with what your rules expect: required documents and fields, confidence on every value, error states and exception flags. Each item gets a position (it checks out, it needs a person, or it is an exception) and the reasons behind it, so a reviewer sees why before deciding whether to agree.
Review
People make the judgment calls.
Exceptions go to your people, with the evidence beside the platform's point of view. Corrections need a reason and are kept in a ledger; nothing is overwritten.
Verify
One record, with the work shown.
A reviewer verifies and locks the record. Every export cites the version it came from, and the reasoning that produced it stays attached.
The same four steps, two ways
A bank statement, which runs through this today, and an underwriting review, which we are building with design partners.
Bank statement
Live1 · Extract
Every account, balance and transaction, with page and row coordinates, from thousands of bank formats and the long tail beyond them.
2 · Analyze
Each transaction tagged with a reason code and rolled up into income, obligations, transfers and coverage. Gaps in the statement history and low-confidence items are called out.
3 · Review
An underwriter opens a flagged deposit, sees the source page, and reclassifies it with a note. The original stays on the record.
4 · Verify
The verified analysis of record, with its version, the reviewer and every correction on it. Exports cite it.
Underwriting review
In development with design partners1 · Extract
The bank statements go through the native engine. The lease, the business licence and what is public about the business online go to the LLM agents.
2 · Analyze
The application says a pizza restaurant, three years in business. Street View shows a pizza restaurant at that address, the web domain is three years old, and the statements show restaurant-supply payments. One exception: deposits run well below the revenue on the application. Point of view: the business checks out; the revenue needs a person.
3 · Review
The underwriter opens the revenue exception, finds that a second account, disclosed late, holds the card settlements, adds it to the file and clears the flag with a note. The point of view updates; the original stays on the record.
4 · Verify
The verified file: every check, the one exception, who cleared it and why. Ready for credit committee or an examiner.
Platform controls
Use it on screen, through the API, or let your AI agents use it through MCP with scoped, audited access.
Design partners
We build products with partners, not projects for clients
Some of our products start with an institution that has a problem worth solving properly. They bring the workflow and the domain knowledge. We build, own and operate the product on our platform, and they help shape it. We work with a small number of design partners at a time.
Who we are
Built by people who have run this work
MoneyStream is led by people who have built and run financial technology at scale, from payments to lending.
4+ hours → 2 minutes
Cash flow underwriting time for 80% of applications, at a private-equity-backed fintech lender
#1
Originator of SBA loans under $350K, on the bank lending marketplace our CTO built
250K
Users of MoneyStream's first product, an AI assistant for household finances, launched in 2012
Get in touch
Talk to MoneyStream
Whether you want to try a product, process more volume, or explore building something together, tell us a little about it and we'll get back to you.
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