It follows relationships
It follows ownership, guaranty, co-borrowing and household ties from record to record, where a report stops at the one in front of you.
Your approved AI assistant reads a governed graph of who owns, borrows, guarantees and shares a household with whom. Read-only, every call logged, every answer followed back to its source file. The decision stays with your people.
Demonstrated on a synthetic book.
The next proof needs your book.
A general assistant sees tables. Yours reads a governed book of who owns, borrows, guarantees and holds what, so it can follow a question the way your people do, and show each step.
It follows ownership, guaranty, co-borrowing and household ties from record to record, where a report stops at the one in front of you.
Every answer names the load it read and the contract it was computed under, and can be followed back to the source file. Evidence, not a score.
Its tools only read, and every call is logged before the answer returns. It cannot sign or record a decision. That stays with your people.
“I'm taking the annual credit review of this business to loan committee. Draw it: its loan, the collateral, and the owners and guarantor behind it.”
$504,988.24 outstanding, no government guaranty; secured by real estate recorded at $681,734.12.
In its words: “Every secondary source of repayment, both the guaranty and the collateral, runs through one person.”
Along the ownership chain, marking which links are recorded and which are only proposed.
Charted against their recorded collateral, from the associated-borrower exhibit for the group.
“Nothing connected to this conversation can record a finding, mark a review complete, or sign the exhibit.” The decision stays with the banker.
From a recorded session on a synthetic book, through read-only tools. Quoted lines are the assistant's own words.
“Before I sit down with this member: is everything they hold with us set up to pass to someone?”
One member, 69 on the date of the extract, with two deposit accounts.
$79,897.94 is held jointly with another member. $16,374.83 has no co-holder, beneficiary or trustee.
And the core records the other member only as a co-holder: how the two are related is not recorded.
Any account with no tie of any kind puts a member at risk. The age floor, the deposit floor and the ties that count are written down, not guessed.
It cannot add a beneficiary or record that a conversation took place. What to raise with the member stays with your people.
From the assistant's read-only tools on a synthetic book. The steps are our summary of what the tools returned; nothing here is quoted.
$492,910.62 to one business, 75 percent guaranteed under SBA 7(a). Its owners are Reese, 57 percent, and Finley, 43 percent. Reese also guarantees the loan.
Finley also owns part of an energy company. So does Sam, who owns 26 percent of a second business with its own loan, $164,955.90, guaranteed by its majority owner, Quinn.
Six businesses and eight people, joined by ownership, co-obligation and guaranty records. Two loans to two different businesses turn out to sit in one candidate group.
$657,866.52 outstanding across the group, $288,183.56 once the SBA-guaranteed portion is netted out, the rule it cites, and a place to record the determination. The lender decides.
One version of every relationship, for every desk.
Your members, businesses, accounts and loans, and the ties between them, in one book with defined meanings, behind the gates below.
Every answer names the load it readEach desk starts with its own work, and leaves a record of what it did.
Relationship managers, business bankers, lenders, branch managers, executives and auditors each see the work for their desk. The people doing the work record what they did.
Auditors and executives read; they do not actAsk in plain language. Every answer names the book it read.
Any assistant that speaks the Model Context Protocol can navigate the book and explain what it finds, through tools that only read. If you connect a cloud assistant, what the tools return is processed by that assistant’s provider.
Read-only tools · every call loggedEach capability is a read-only tool your assistant can call, on a synthetic book today.
The rules for AI are still being written, but your examiner will expect you to understand how the AI works and how its answers are supported. Six gates stand between your files and an answer, and each is in the code. Proven end to end on a synthetic book.
A column is used only by its exact name, or by a written, dated ruling from your team.
Each ruling carries a name and a dateEvery kind of member, business, account and relationship is defined once, in words, and linked to the industry’s open ontology where it has a term.
FIBO references checked against a pinned release, none failingA full load is graded against the contract before it answers a single question.
26 checks grade a full loadEach rule test plants the error it must catch, so a rule that stopped working would show.
552 planted errors, every one caughtEvery call is logged before its answer is returned. The assistant can read your book, never write to it.
If the log cannot be written, no answerGroups are candidates. The assistant cannot sign; your authorised signer records the determination.
The signature records the signer’s roleProven on a synthetic 160,000-member book with contract 8.2. Ontology references checked against FIBO release 2026Q2; rule tests from committed evidence, 24 September 2026.
We’ll walk through a connected-borrower or household example on the synthetic book, review which records your exports could supply, and decide together whether a scoped evaluation makes sense.
Discuss an evaluation ↗First conversation: your question and a file-and-column list. No customer data. Our demonstration films are available on request.No customer data is needed for the first conversation. Send only a file and column list. Data access and handling for any pilot would be agreed separately.
Customers and accounts are the required starting files. Additional records determine which relationships and answers can be supported. We review your columns rather than promise a fixed tier.
Not yet. We are in active conversations with several credit unions. The demonstrated path runs on a synthetic book. It is built to run in your environment; deployment at an institution still needs to be proven.
No. The current demonstration uses synthetic data. Before any evaluation involving member information, we would agree the scope, access, hosting and security requirements with your team. Proceeding would depend on your institution’s approval.
It presents candidate groups and supporting evidence. The institution makes the determination. A single-borrower group can still have an exhibit.
A lender, someone who knows your core, and us. Who takes part and how much time it asks are agreed in writing before an evaluation starts.
Terms, including any cost, are agreed in writing before an evaluation starts.
It depends on which of three configurations you run. Dashboard only: the stack runs inside your environment and makes no outbound calls. MCP with an assistant your institution has approved: whatever the tools return goes to that assistant, and so to its provider, under your agreement with them. Embedded assistant: the stack itself sends approved content to the provider you configure, and no more than that. Our demonstration runs the embedded assistant on a synthetic book. The dashboards work in every configuration without an assistant.
The stack is built to run inside your own environment. Whether it makes any outbound call is a configuration choice, stated above and agreed before starting, as are where it runs and who operates it.
What happens to any data and any copy is written into the agreement before we start.
Local proof is a milestone.
Customer validation is still ahead.
Answers from every tool, captured twice and compared: the same answers both times.
LOCAL VALIDATIONFive minutes, from files to a traced answer. Every spoken line is backed by our code or a cited source.
FILM