Month-End Close

Month end close automation that shaves days off the close.

We build AI agents that prorate the invoices crossing your close boundary, dedupe the related vendor bills, and propose AP accruals for review — so your books close days sooner.

  • AI implementation services
  • AI agents in your cloud
  • Your close calendar, encoded
  • Staff approve before anything posts

Built with the leading AI platforms

NVIDIAAnthropic
Peter Enestrom, founder of Zaigo

Led by Peter Enestrom and the Zaigo AI & engineering team

YaleColumbia UniversityMicrosoft

The broken Friday

AP accruals take two or three days of the close.

From finance teams we have sat with: CFOs and controllers at multi-branch healthcare and services companies, where the close calendar is fixed and the accrual work is not.

  • Two or three days on AP accruals

    Every month, two or three days of the close period go to AP accruals: finding the bills that cross the boundary, splitting them across periods, proposing the entries. The calendar does not move; the work does not shrink.

  • The prorate is done by hand

    An invoice that spans two months gets split by a person with a spreadsheet — branch by branch, line by line. Multiply that by every entity you close.

  • The same vendor, billed twice

    Related invoices from the same supplier arrive separately and get deduped by eye at the busiest point of the month. Miss one and the accrual is wrong.

  • No way to check the pricing

    The bills keep coming, and nobody has a way to check that every line matches the supplier price file. The overcharge surfaces long after the money left — usually as a next-month adjustment.

  • The entries still get keyed

    After the accruals are agreed, someone keys the journal entries into the GL by hand — the last manual step of a manual process.

  • “We need to get our books closed quicker”

    Heard from the CFO of a multi-branch care provider. The close is not slow because the team is slow — it is slow because the work waits for people who are already full.

What manual costs

Two or three lost days is a reporting delay, not an inconvenience.

What the manual close looks like at a multi-branch provider. Your numbers will differ — tracing one close cycle puts figures on yours before anything gets built.

2–3 daysOf every close period spent on AP accruals at one multi-branch care provider
By handHow invoices crossing the close boundary get prorated today — per branch, per line
Next monthWhen a missed accrual or a duplicate bill surfaces: after close, as an adjustment

From an anonymized engagement — the CFO of a multi-branch hospice and home-health provider

How it works

Accrual automation: we encode your close calendar.

No new system for your team to learn. The checks your best accountant runs at month end become the system — AI agents run them, people approve the entries.

  1. 01

    Trace one close

    We follow one month-end close: which invoices crossed the boundary, how accruals were proposed, where the two or three days actually went.

    Weeks 1–2
  2. 02

    Encode the close rules

    Proration logic, dedupe rules, accrual thresholds, approval routing — documented against your close calendar and your GL, encoded as rules you own.

    Yours to keep
  3. 03

    AI agents draft the accruals

    Each boundary invoice is prorated, related vendor bills deduped, and accruals proposed for staff review. Approved entries batch-upload into Sage Intacct or your GL.

    Every close
Not another license

Balance sheet reconciliation software rents you the checklist. Your close rules are the product.

Close software ships checklists, task trackers, and a dashboard of what is late — licensed per seat, configured by your team. It can tell you an accrual is due; it cannot build the accrual, because it does not know your proration rules or your vendors.

We build AI agents that run in your cloud, against your invoices and your GL, on rules encoded from your close calendar. You own the IP; proposed accruals reach a person with the working attached, and only approved entries post.

Peter Enestrom, founder of Zaigo
Who builds it

Led by Peter Enestrom.

Co-Founder — leads AI & Engineering

Pete Enestrom

Every engagement is led personally by Pete, working with the Zaigo AI & engineering team from the two-week audit through the production handover. The person who scopes the work is the person who builds it.

Education
Yale & ColumbiaGraduate
Background
Microsoft & IntelFormer
Experience
Exited FounderVenture-Backed

Background

Questions

Asked about financial close automation.

The straight answers, before you book anything.

What’s holding your business back?

A workflow ready for automation. An AI product you want to build. A problem that has sat on the roadmap for years. Let’s talk about what it would take to solve it.

Talk to Zaigo