AI for compliance & audit, with the evidence built in
The worst part of compliance isn't the rules. It's proving you followed them. We build workflows where policy is enforced in the work itself and every action lands on a record your examiner can walk.
Built for
Compliance officers
General counsel
Risk teams
Internal audit
Regulated operations leaders
Learn more
The Challenge
Being compliant is one job. Proving it is another.
Controls, attestations, filings, findings, remediation. The calendar lives in a tracker somebody maintains by hand, the scope test lives in one person’s head, and the evidence never quite ties to the register.
control_calendar_Q3.xlsxMOSRAV+1 editing
Without an agent
With an agent
01The obligations
Nothing tells you a control slipped.
Recurring work sits in a tracker someone updates by hand, so the one gap surfaces late.
02The scope test
Whether it’s reportable gets re-argued every time.
The test lives in one head, so the same facts land differently three months apart.
“Is this one reportable?”
Last quarterYes
In MayNo
This oneWaiting
With AI in the mix
One written test, applied the same way, with the reason attached to the record.
71 prior calls read
03The evidence count
The evidence never adds up to the register.
Three places hold the count, and closing the gap is a week of screenshots.
Register148
Folder141Δ
System log148
With AI in the mix
All three148
Reconciled control by control, with the missing evidence named.
…and many more use cases
Capabilities
The AI our clients actually put to work
Not a product menu. These are the capabilities we design, prototype, and ship inside your operation, in whatever combination the work calls for.
Document & data extraction
Any document you handle, turned into usable data.
Regulated docs and filings
Checked against your controls
Written to your systems
Agentic workflows
Multi-step work that runs start to finish.
Controls executed in the workflow
Approvals where policy requires them
Exceptions routed to a person
Decision support
Faster calls, with the evidence already attached.
Your control criteria, encoded
Evidence surfaced up front
Judgment stays with your team
Risk, compliance & audit
Oversight that builds its own paper trail.
Exceptions flagged as they happen
Policy enforced at the point of work
Actor, time, and reason logged
Reporting & analytics
Reporting that renders from the source, not by hand.
Evidence packs assembled on demand
Lineage on every number
Your team reviews, not rebuilds
Conversation & voice
Client conversations handled in plain language.
Auditor requests answered from the record
Full context from your systems
Resolved or escalated cleanly
Your own operating platform
The interface your team has always dreamed of. It now costs less to build than to keep renting your way around it.
One interface, not six logins
No per-seat bill as you grow
AI inside the work, not beside it
Most teams put three or four of these to work. A Jumpstart finds which ones earn their place, on your own files, before you commit to a build.
Case study
Compliance that records itself
Loans, brokers, commissions, and compliance on one operating layer
A specialty lender replaced spreadsheets, email queues, and manual ledgering with one system, where every loan-life event is journaled with actor, timestamp, and reason. Audits went from quarterly fire drills to read-only checks, and capital partners get the trail they ask for, on demand.
You already have policies, approval chains, and an examiner who checks all of it. We build inside your rules. That shapes the work from day one, instead of becoming a checklist at the end.
We build to your rules
Your approval chains and record-keeping rules go in from day one. If your policy says a person signs off, the system enforces it.
Not our first rodeo
Our team has worked with personal data, SOC 2 requirements, and records a regulator can ask for. Yours won't be the first security review we've answered.
You own everything we build
The code, the accounts, and the documentation are yours. Nothing to hand back at the end, and the architecture is your IP to use forever.
Where to start
One workflow, one team, or the whole department
Some teams arrive with one process that's breaking. Others want to rebuild how the department runs. We meet you where you are.
Start here
AI Jumpstart
A few weeks to map how the work really moves, audit your stack, your data, and your controls, and find where AI pays back. Delivered with a working prototype on your own files, before anyone commits to a build.
Your prototypes built into production software by a lean team that stays through launch, rollout, and your first audit on the new system. The code is yours, in your own accounts.
No. AI does the checkable work: it reads documents, matches records, flags exceptions, and assembles evidence. Decisions that need a person and a documented reason get one, and the system enforces that. If your policy says a compliance officer signs off, the workflow doesn't move without the sign-off, and the record shows who gave it and why.
What does the audit trail actually capture?
Actor, time, and reason on every event, tied back to the source documents. When a file moves, a control runs, or an exception gets cleared, the record shows who did it, when, and on what basis. Because the trail is designed alongside the workflow rather than reconstructed afterward, answering a request means reading the record instead of rebuilding it.
Will this satisfy our examiner?
We don't speak for your examiner, and we'd be wary of anyone who does. What we build toward is a simpler claim: when the question comes, your answer comes from the record, not from a scramble. Policy enforced in the workflow, exceptions flagged when they happen, and evidence assembled on demand tend to make those conversations shorter.
What about model risk and explainability?
The work we give AI is the checkable kind: extraction, matching, routing, and assembly. Every output carries its source, so a reviewer can trace any field back to the document it came from and confirm it in seconds. Nothing in the system asks you to defend a judgment a model made, because the judgments stay with your people.
What's the first control worth automating?
The control you're proving by hand today. The one where evidence means screenshots and exports is usually the one where a built-in trail pays back first. A Jumpstart maps how that work really moves, audits the stack and the data behind it, and proves the approach with a working prototype on your own files.