Firms with a growing AI bill
You spend thousands of dollars a month on AI seats and usage and want to know what each part of it returns.
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We review what your agents and AI seats cost and how well they do the job, then cut the waste and set up tests so quality holds as things change.

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Some firms now spend tens of thousands of dollars a month on AI, across seats and agents that were added one at a time, and it's hard to tell which parts are worth the money. We measure how well each agent does its job and where the spend goes, then change one thing at a time and test after each change, so you can see what it did to cost and quality.
Tagging an email and drafting a contract often run on the same top-tier model at the same rate, when a smaller, cheaper model could handle the simple work.
A seat costs the same whether it's used or not. In a trial Microsoft ran across 66 firms, average weekly use of its AI assistant over the last three months ran from 6.3% of licensed staff at one firm to 70% at another.
Documents go out of date and providers update their models. Without a set of test questions, nobody sees answers getting worse until a wrong one reaches a client.
We measure your current setup before touching it, so every saving can be checked against where you started.
We go through your AI bills and usage reports and tie each cost to an agent or a seat, which shows what each one costs you a month.
We collect real questions and tasks from your team, with the answers they should get, and score your current setup on them before we change anything.
We tighten the instructions each agent runs on and clean up the documents it searches. Workflow steps that run twice or add nothing come out.
Simple jobs like sorting and tagging move to smaller models. Long instructions an agent sends with every request get cached, so you pay less each time they repeat.
A weekly report tracks cost and test scores, so a drop shows up the week it happens. We cancel seats with no use in four weeks or move them to people who've asked for one.
You spend thousands of dollars a month on AI seats and usage and want to know what each part of it returns.
An agent worked well at launch, but now people double-check its answers or ignore them, and nobody knows what changed.
Your own staff or another firm built your agents, and you want an outside review before you spend more on them.
Your AI line keeps growing and you need to show what it returns before the next renewal or budget round.
Still deciding? On a free 30-minute call we'll tell you what fits.
A change only stays if it scores as well as before on your own test set. We score your current setup first, so a smaller model has to prove itself on your real tasks.
It depends on how many seats sit idle and how much simple work runs on large models. We estimate the saving from each change after the review, before you commit to any of them.
With a test set of real questions from your team and the answers they should get. Stanford researchers found legal research tools built on retrieval still gave wrong or unsupported answers 17% to 33% of the time, so we measure your own rate.
Whichever ones your agents use today. We choose a model for each task on its test score and its price, which can mean using more than one provider or model size.
About 3 to 4 weeks, depending on how many agents and seats you run, and we quote it after the free call. Every change happens in your own accounts, and we write each one down.

Research · 6 min read
Use of paid AI seats peaks soon after launch, then settles lower. In a large Copilot trial, a worker's employer predicted their use better than their own work habits did.

How it works · 7 min read
A company AI brain searches your files, hands the closest passages to a language model and has it write an answer with citations. Your sharing settings decide what it can see, and your documents decide how often it's right.

On a free 30-minute call, tell us roughly what you spend on AI and what your agents do. We'll say where we'd look first and what a review would involve.