AI, with receipts.

Turning AI investments into improved business performance, one workflow at a time.

Map the value Redesign the workflow Deploy the system Report the result

Tell us how we can help See a worked example

How every engagement is judged

The workmanual

Overdue invoices, chased by hand when someone has time

The AIagent · running

An agent follows up daily, escalates exceptions to a human

The receiptcleared

Paid ~9 days sooner — visible in the bank, not a dashboard

Illustrative figures — we model yours before anything is built. If the ROI math doesn't clear, we tell you.

The gap between buying AI and getting measurable impact from it.

Most companies don't see a strong business impact from AI because it's being treated as tech to "install" instead of a set of changes to how work is done and how value is created.

[ The productivity trap ]

100 hours your team got back this quarter

~76 hrs reabsorbed — busier, not better

~24 hrs converted to a number that moved

Freed capacity isn't value created. Until the work is redesigned around it, the saved time just refills with more low-value work.

01
The pilot that got the green light hasn't actually made a measurable impact.
02
Hours saved across the team are filled with more low-value tasks.
03
Adoption charts climbing while business KPIs remain unchanged.

You didn't invest in AI for activity. You invested for a result. Here is how we get you one.

[ What we do ]

Two tracks. One standard.

Whichever track fits, the goal is the same: turn the AI you've bought into business performance you can measure. Pick where to start, and one rigorous method runs underneath both.

Built on Claude

Workflow Automation

Most teams already pay for Claude and mostly chat with it. We turn it into production: custom plugins, skills, and agents that take the manual work off your team and run on the tools you already own.

~15 hrs/wk of manual work taken off a team

Plugins, skills, and agents. Composed for the work your team actually does, connected to your systems through MCP.
Drudgery, automated. Recurring exports, reconciliations, and follow-ups that run themselves, with the workflow around them optimized.
Productivity you can measure. Fast gains for operations, sales, and finance teams, the kind you can put a number on.

Decision Intelligence

Your dashboards tell you what happened, rarely why. We wire Glean into your data so the notes, tickets, and remarks no chart reads sit alongside your structured numbers, and anyone can ask in plain language to get the root cause.

~5–8 min to surface an answer that took analysts days

The why, not just the what. Dashboards only answer the questions they were built for. Glean reads the structured data and the unstructured detail underneath it, surfacing the reason a number moved.
Minutes, not a week. What took an analytics team days of pulling data and reading remarks comes back in minutes, so the call gets made the same morning.
Natural language in, dashboards out. Ask in plain language, get a sourced answer, then build or refresh a dashboard inside Glean. No SQL, no BI ticket, no analyst queue.

[ How we operate ]

The AI Impact Engine

Whichever track you're on, the same method runs underneath: the Impact Engine. It's our ROI-focused way of turning fragmented data and one-off experiments into a living system that moves a number you can measure. We align on what matters, map the drivers, build targeted solutions, prove the impact, and operate it continuously.

01

Align

Each engagement starts with working sessions to understand your top-tier metrics, the key drivers underneath them, and the workflows that influence them.
02

Map

Before building anything, we map where decisions actually get made, the systems involved, and identify the biggest opportunities for AI impact.
03

Build

We design intelligent agents and reimagine workflows around the decisions and drivers we mapped, each one explicitly tied to the metrics that matter most.
04

Prove

The Impact Engine becomes your live map of impact, showing which workflows are active, which drivers they're moving, and exactly how those ladder up to revenue, margin, efficiency, and risk reduction.
05

Operate

We run the system continuously: ongoing optimization, new use cases, additional agents, training, and support. The engine doesn't just ship; it runs and evolves with your business.

Operate loops back into align. The engine keeps surfacing the next number worth moving.

Why teams pick us.

We name the number first

Every engagement commits to a metric before work starts and reports it after, including when the result is unflattering. That's the deal, in writing.

measured, not promised

We redesign the work, not just bolt on AI

We come from process intelligence. Tools dropped onto a broken process inherit the breakage. We fix the workflow first, then deploy.

Priced against the number, not the clock

No hourly billing anywhere. If the model doesn't clear our fee with room to spare, we tell you.

Platform-agnostic by design

We bring the right tool for the problem, whether that's our Impact Engine, Glean, Claude, or something simpler. We don't pitch one vendor at every problem.

Everything is yours

The map, the model, the system, the scorecard: built on your accounts, documented for your team, with no dependency on us.

We stay until it holds

Launch isn't the finish line; the metric holding is. Post-launch support lasts as long as it's useful, and not a day longer.

You have questions, we have answers.

Start with the problem, not the tool. Workflow Automation fits when repetitive manual work is eating a team's week and you want it taken off them. Decision Intelligence fits when you have the data but not the why behind the numbers. Many teams start with one and add the other. The Impact Engine runs underneath either, so the method is the same whichever you pick.

Most pilots prove the tech works and stop there. The hours come back, then refill with more low-value work, and the business number never moves. We start from the number, redesign the workflow around it rather than bolting AI onto a broken process, and report the result after, including when it's unflattering. If a number can't be moved, we'd rather tell you before the build than after.

It helps if you do, and most teams already pay for Claude and mostly chat with it. We're a Glean partner, so we can provide and implement Glean directly; for Claude we work with the license you already own rather than reselling it. Either way we lead with the outcome, not the sale, so if a simpler tool moves your number, we'll tell you.

We model the number before anything is built, so you know in the first weeks, not after a quarter, whether the ROI clears. From there the build is scoped to that metric and shipped in focused increments, so the first measurable result lands early rather than at the end of a long engagement.

The workflow map and the ROI model come first as a fixed fee, and you can take both and walk away. Build and support are priced against the modeled value of the metric, agreed in writing before we start. No hourly billing anywhere. And if the model doesn't clear our fee with room to spare, we tell you to keep your money.

The system runs on your accounts and your infrastructure, so your data stays yours. Everything we build is documented for your team with no dependency on us. We support it past launch for as long as that's useful, and the map, the model, the system, and the scorecard are yours for good. If we did the job right, you don't need us until the next number.

[ Start here ]

Ready to see where AI can improve your business?

Get a free value assessment. Pick a number you'd like to move and we'll model what AI could do with it and what that's worth. No commitment, and if it isn't worth doing, that's the answer you'll get.

Numbers people bring us

Illustrative

Days from invoice to cash

64 53 days

−11 days · working capital freed

how: follow-up goes daily instead of when-someone-has-time — modeled on your volumes in session one

Get your free assessment

No deck. No pitch. No commitment.