Finance & Insurance
Credit memo assembly, reconciliation and close, alert triage, onboarding files, statement ingestion and regulatory evidence — built so that the system assembles and a licensed human decides.
The decision is not the bottleneck. Assembling the evidence the decision rests on is the bottleneck, and it is clerical, high-volume work that nobody enjoys and everybody is doing by hand.
Workflows
What we automate, and where it stops
Every one of these ends one step short of the decision. In a regulated industry that is not caution, it is the architecture — and it is what makes the work approvable.
Credit memo and underwriting pack assembly
Financial statements, bank data, filings and correspondence turned into a structured draft with every figure traceable to the page it came from. Extraction confidence is calibrated, and a low-confidence field is left blank and flagged rather than filled with a plausible number.
Stops at: A credit officer approves. The system never scores and never decides.
Built with AI & Applied ML
Reconciliation and month-end close
Continuous matching across the ledger, bank statements and payment processors, with everything that does not match surfaced as a ranked exception queue carrying the evidence for each break.
Stops at: An accountant clears each break. Nothing is auto-written-off.
Built with Platform & Data
KYC and AML alert triage
Each alert arrives with its supporting evidence already assembled and a written rationale for its position in the queue — so the analyst spends their time on the judgement rather than on the gathering.
Stops at: An analyst dispositions every alert. None is ever auto-closed.
Built with Agentic Systems & Automation
Client onboarding and suitability documentation
Identity, source of funds, risk profile and suitability evidence assembled into a file that is either complete or explicitly short of named items. No silent gaps.
Stops at: An adviser signs. The system assembles the file; it never advises.
Built with AI & Applied ML
Statement and portfolio data ingestion
Custodian statements, broker exports and screenshots turned into typed holdings, each carrying the document and page it came from. Rows the model is not confident about are refused and queued rather than guessed.
Stops at: Refused rows go to a person. A guess is never written as a holding.
Built with Platform & Data
Regulatory reporting and evidence trails
Periodic returns assembled from their sources with the derivation of every figure recorded — so the question "where did this number come from" has an answer that does not depend on who was on the team at the time.
Stops at: A compliance officer submits. The trail is as much the deliverable as the report.
Built with Platform & Data
Constraints
What is actually hard here
There are no client names, logos or percentages on this page. Until there is a real figure with permission to publish it, the space is better spent on the difficulties we can defend.
Nothing decides
Every workflow above stops one step short of the decision, with a named role at the stop. That is the architecture, not a disclaimer — it is what makes the work approvable by a compliance function in the first place.
Read the long versionThe control has to survive an audit
A control that exists only in a reviewer’s habit is not a control. Evidence, segregation of duties and change management are designed in rather than reconstructed when somebody asks.
Read the long versionA model’s output is a claim until it is measured
Extraction and classification are graded against a held-out set that is never used to build the system, so an accuracy figure means something. Without that, a number is an assertion.
Read the long versionMeasuring and training must not share a dataset
The moment the set used to check the system is also used to improve it, the score stops being information. In this industry it also hides the difference between what past decisions did and what a reviewer believes correct today.
Read the long versionVerification is the work
Generating a draft is cheap and checking it is not. Capacity planning that assumes otherwise produces a pile of unreviewed output and calls it throughput.
Read the long versionThe demo is not the system
Document workflows demonstrate beautifully on three clean examples and fail on the fourth, which arrives as a scan of a fax. The difficult cases are the project.
Read the long versionBring us the workflow, not the brief.
Describe what your team does by hand today and where it backs up. We will tell you which part is assembly, which part is judgement, and which of the two we would touch.