I build AI automation for finance teams.

I've spent my career in finance: consulting, investment banking, and now strategic finance. I know what the board pack, the variance pack and the close cost a small team every month.

I turn those recurring deliverables from manual assembly into automated refresh plus review, with independent checks before any number leaves the team, and a runbook so your team can run it without me.

Let's talk
A storybook illustration of Jake riding the subway at night with a laptop open on his knees, its screen lighting him up.

What I do

the short list

How it works

founding clients at pilot pricing

The workflows

before and after

Board reporting

The usual way
Most board packs are assembled by hand. Numbers get copied from the model, the forecast and the ledger into slides, bridges are rebuilt each quarter, and figures that appear on more than one slide are cross-checked by eye.
What I build
A backing workbook for each meeting with one tab per slide, charts linked into the deck, and the standard bridges (plan vs prior plan, forecast vs actual) built from the same sources every time.
How it's checked
A tie-out runs before the deck goes out. It traces every figure to its source, confirms the bridges sum, and flags any number that differs between slides.
You end up with
Board prep that is review, not assembly. Inconsistencies get caught before the meeting, not in it.
How it fits together
  1. Your sourcesmodel, ledger, bank, KPI exports
  2. Backing workbookone tab per slide
  3. Tie-out
  4. Decklinked charts

FP&A variance reporting

The usual way
Monthly actual vs plan commentary is pulled by hand from a large workbook, and the explanations are written from memory.
What I build
One pipeline that pulls actuals and plan line by line, flags what moved, and drafts the "why" from the ledger: which accounts and vendors drove each variance. Volume, mix and rate are separated where there is unit data.
How it's checked
Every account must be mapped, actuals must tie to the ledger total, and the pieces of each variance must sum before a pack is produced. Anything the ledger can't explain comes to you as a question, not a guess.
You end up with
The same pack every month, with explanations that tie to the books and no re-keying.

Getting budgets into the projection model

The usual way
Department budgets arrive in spreadsheets with their own layouts. Mapping them into the model is manual and easy to get wrong.
What I build
A mapping layer from budget submissions to your model's account structure. It handles parent and leaf accounts so nothing is double counted, applies your plan-period rules, and supports labelled splits that tie back to the total.
How it's checked
Each submission's total must equal its mapped total, and every split shows its difference against the model, which should read zero.
You end up with
Budget-to-model tie-outs become a check, not a project.

Building financial projection models

The usual way
A large workbook with hard-coded links. Inputs drift, fixes break other tabs, and each scenario is another copy of the file.
What I build
It starts with an audit of the model you have. Then a rebuild in layers: actuals in clean tables, a driver-based forecast at the grain you plan on, scenarios as toggles, and a frozen snapshot of each approved plan.
How it's checked
The rebuilt model is tied to the old one line by line before it replaces it. Actualized periods must equal the ledger, and a test run follows every change.
You end up with
One plan of record, faster scenarios, and reports that refresh from the model instead of being re-keyed.

The monthly close roll

The usual way
Rolling the forecast forward after close means pasting actuals, matching cash by hand and reconciling in side spreadsheets.
What I build
A scripted, checklist-driven roll from the closed books into the forecast, with a changelog and a decisions register for every judgment call.
How it's checked
Cash must equal the bank, the model must equal the trial balance, and every gate must read zero before the roll is accepted.
You end up with
A shorter gap between close and an updated forecast, with an audit trail for every change.