AI for finance teams, with lineage on every number
The close shouldn't be a forensic exercise. We build the AI agents, automated workflows, and software that carry the matching, chasing, and assembling, so your team reviews numbers instead of rebuilding them.
Built for
CFOs
Controllers
FP&A
Finance operations
Billing teams
Learn more
The Challenge
The accounting system is clean. The close is not.
AR, AP, payroll, revenue, intercompany. The queue that runs the close sits outside the ledger, the treatment calls wait on one person, and the sub-ledger, the GL and the bank still disagree.
close_checklist_AUG_v6.xlsxMSAVPL+2 editing
Open item
Area
Amount
Why it’s open
Days
Aging · 90+
AR
128,400
Credit memo or write-off
6
Vendor accrual
AP
74,500
No invoice received yet
1112
Off-cycle run
Payroll
43,900
Landed after cut-off
3
Deferred rev
Revenue
216,000
Contract term unclear
8
IC transfer
Interco
31,200
Booked on both sides
5
Without an agent
With an agent
01The open items
The close runs on a sheet, not the ledger.
Your ledger posts the routine entries. Every open item gets chased somewhere else.
02The treatment call
One person decides how it books.
Accrue it or not, capitalize it or expense it. The answer moves with whoever is in.
“How did we book this last time?”
Q1Capex
Q2Expense
This oneWaiting
With AI in the mix
The same test books it every period, and the reasoning sits on the entry.
52 treatments logged
03The variance
The sub-ledger and the GL never match.
Finding the one entry that explains it takes a day of digging through both sides.
Sub-ledger812,640
GL809,115Δ
Bank812,640
With AI in the mix
All three812,640
Reconciled daily, with the entry behind every variance 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.
Invoices, statements, and POs
Checked against your rules
Written to your ledger
Agentic workflows
Multi-step work that runs start to finish.
AR and AP chases, end to end
Approvals where you require them
Exceptions routed to a person
Decision support
Faster calls, with the evidence already attached.
Close checklists, evidence attached
Support surfaced up front
Judgment stays with your team
Risk, compliance & audit
Oversight that builds its own paper trail.
Approval thresholds enforced
Policy applied in the workflow
Actor, time, and reason logged
Reporting & analytics
Reporting that renders from the source, not by hand.
Built from live data
Lineage on every number
Your team reviews, not rebuilds
Conversation & voice
Client conversations handled in plain language.
Vendor and billing queries
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
A quarter close that reaches investors in days
Investor reporting rendered from the source, not rebuilt by hand
A commercial real estate firm closed its quarter across property software, Excel rollups, and hand-assembled investor packs, and the rollup took the same two weeks every time. We built one operating layer that renders the report straight from the source, so the book grew without the finance team growing with it.
You already have approval thresholds, segregation of duties, and auditors who ask for support. We build inside them. 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.
It drafts and matches; posting follows your approval rules. If your policy says a journal entry needs a person's sign-off, the system routes it to that person and records the approval. AI never makes a call your team would have to defend without a documented reason behind it.
What about accuracy?
Every extraction and every match is checked against your rules before it touches anything downstream. Whatever doesn't clear those checks routes to your team as an exception instead of slipping through quietly. And every action is logged with its support attached, so if a number is ever questioned, the answer is a lookup rather than an investigation.
Will our auditors accept this?
They'll tell you, but here's what they'll be looking at: an actor, a time, a reason, and a source document on every number. The trail isn't a feature we bolt on; it's the point of the build. In practice, pulling support for a sample stops being a scramble through inboxes and becomes a read-only exercise.
Does this replace our ERP or accounting system?
Usually not. Your accounting system handles the standard entry well, and ripping it out is rarely the highest-value move. What we build is the layer around it: the extraction that fills it, the exception chasing it was never designed for, and the reporting it can't produce on its own.
Where do finance teams usually start?
The close and AR, most often, because that's where the manual hours pile up. A Jumpstart is a few focused weeks to map how the work really moves, audit the stack and the data behind it, and prove which piece pays back first, on your own files, before anyone commits to a build.