Running on the desk

categorize · classifies every transaction against your chart of accounts · continuous ▸ reconcile · three-way match across bank, processor, and ledger · daily ▸ cashflow · 13-week forecast rebuilt from live data · weekly ▸ anomaly · every account diffed against its rolling baseline · daily ▸ sales-tax · taxable data normalized against jurisdiction rules · monthly ▸ stack · TypeScript · Postgres · Cloudflare Workers · Claude · OpenAI ▸ categorize · classifies every transaction against your chart of accounts · continuous ▸ reconcile · three-way match across bank, processor, and ledger · daily ▸ cashflow · 13-week forecast rebuilt from live data · weekly ▸ anomaly · every account diffed against its rolling baseline · daily ▸ sales-tax · taxable data normalized against jurisdiction rules · monthly ▸ stack · TypeScript · Postgres · Cloudflare Workers · Claude · OpenAI ▸

An AI implementation firm for your back office

Your back office, run on AI.
We build it, we implement it, we run it.

PC Financials builds and implements the AI, fixes the systems underneath it, and runs what comes out: the data, the reporting, the books. One firm, from the CRM to the board packet.

For operators who know AI belongs in the back office and don't want to guess where it goes · Outgrown a bookkeeper, watching competitors move faster

Book a 30-minute intro → See how it works

The problem

One operation,
not three vendors.

Most growing companies don't have a books problem or a reporting problem. They have a fragmentation problem: a bookkeeper here, an outsourced "CFO" there, a CRM that doesn't talk to the GL, and no one accountable for the whole. The numbers are late, the reports are unreadable, and the seams are where the truth gets lost. They also know AI should be doing more of this, and can't tell you where it goes, who would implement it, or what breaks if they get it wrong, while the competitors who worked it out are pulling ahead. We replace that with one operation that runs from the CRM and the ledger up to the boardroom, with AI we build and implement and systems we fix and own.

The data never agrees

The CRM says one thing, the processor says another, the ledger says a third. Every number needs a person to reconcile it before anyone can trust it, so nothing is current and everything is contested.

II.

Nobody owns the seams

The bookkeeper owns the books. The CFO owns the reporting. Nobody owns the gap between them, and that gap is where the truth goes missing.

III.

AI has nothing to run on

Pointing a model at a chart of accounts that cannot answer the question produces faster wrong answers. This is why most AI pilots in finance quietly stop after a quarter.

IV.

You find out too late

By the time a bad month shows up in a report, it is two months old. The decisions that would have changed it have already been made.

The method

Nothing here is off the shelf.

We write a small set of named agents against your actual systems, your real chart of accounts, your real workflows, and we own the code they run on. We fix the integrations underneath them and automate what connects them. They run on schedule, and every edge case goes to a queue a human reviews. Nothing is resold, nothing is a bot you rent, and nothing gets configured once and abandoned.

Operating principle

"The model is the easy part. The hard part is the scaffolding around it: the checks that catch the failures, the queues that surface them, and the path back when something goes sideways at 3am."

Pin Cohen, CPA

Agent	What it does	Cadence
categorize	classifies every transaction against your chart of accounts	continuous
reconcile	three-way match across bank, processor, and ledger	daily
cashflow	13-week forecast rebuilt from live data	weekly
anomaly	every account diffed against its rolling baseline	daily
sales-tax	taxable data normalized against jurisdiction rules	monthly

Agents are tuned per engagement, run on schedule, and write proposed entries to a queue a CPA reviews, never straight to the ledger.

In practice

What this looks like in practice.

Before

Two CRMs that didn't talk to each other, and neither talked to the ledger. On top of that, a bookkeeping firm that wasn't delivering and an outsourced CFO producing reports nobody could use. Money moved through the business and the owner couldn't say why.

What we did

We made the two CRMs work and talk to each other, then wired one process running from the CRM through the ledger to reporting. Once the data had somewhere coherent to land, we built the AI in where it added leverage, not everywhere, only where it counted. Then we replaced the parts of the finance operation that weren't working and cut what wasn't earning its place.

After

A finance operation the owner can see and trust. He knows why there's money in the bank.

How it runs

What the first
five weeks look like.

Most engagements run the same shape. The dates slip; the steps don't.

Intro call

Thirty minutes. No deck. We map your stack, the close calendar, and the two or three things that hurt most.

Week 0

Written scope

A single-page scope arrives within five business days: fees, deliverables, what isn't included.

Week 1

Discovery & migration

Two weeks of pulling data, mapping the chart of accounts, and standing up the first agents.

Weeks 2–3

First close

Your first clean monthly close, the board packet, and the cash forecast. Signed off by business-day 7 of the month; we post-mortem the day after.

Weeks 4–5

Steady state

Quarterly business review. Annual scope refresh. Software and books stay one engagement.

Ongoing

Before you call

Five answered

Where does our data actually go?

Into a staging database this firm controls. Model calls run through commercial APIs, which do not train on submitted content, and no client's data is ever pooled with another's. The agents read against a copy; anything written back to QuickBooks or Xero is explicit and logged, and every proposed entry waits in a staging table for review before it reaches your production ledger.

Who owns the code, and what do we keep?

PC Financials owns and maintains the agent code. You get the outputs, the staging-table audit trail, and a written runbook for each agent, not the source. Systems work ends in either ongoing maintenance or a clean handoff, your call, so the integrations do not become a hostage.

Can we start with just the AI and systems work?

Yes. Those two lines are sellable on their own, and we'll implement them against your existing finance team's work. They're also the engine when we run the whole operation.

Our books are already behind. Is that a problem?

It depends how far behind, and we'll tell you on the intro call rather than guess. Catch-up is real work, so it's scoped and quoted separately from the ongoing engagement instead of being buried in it. What we won't do is quietly start a clean close on top of periods that were never right.

Can you replace our controller?

Sometimes. If the controller is mostly running close and reporting, yes. If they're in a finance-leadership role doing FP&A, fundraising, or board-facing strategy, you want both.

Do you sign an NDA?

Yes. Mutual NDA before the intro call if your stack requires it, standard otherwise.

Your back office, run on AI.
We build it, we implement it, we run it.

One operation,
not three vendors.

Nothing here is off the shelf.

What this looks like in practice.

What the first
five weeks look like.

What's inside the engagement.

Where we go deep.

Notes from the work.

How to automate your bookkeeping in 2026

Book a call.
Thirty minutes, no deck.

Your back office, run on AI. We build it, we implement it, we run it.

One operation,not three vendors.

Nothing here is off the shelf.

What this looks like in practice.

What the firstfive weeks look like.

What's inside the engagement.

Where we go deep.

Notes from the work.

How to automate your bookkeeping in 2026

Book a call. Thirty minutes, no deck.

Your back office, run on AI.
We build it, we implement it, we run it.

One operation,
not three vendors.

What the first
five weeks look like.

Book a call.
Thirty minutes, no deck.