Build on what you know.
We help your team organize its information, put AI to practical use, and build on each result.
Senior-led delivery. On retainer.
See the capital stack across scattered filings.
A single deal is spread across messy filings and disclosures. We bring the pieces together, show what the record supports, and keep the unknowns visible.
The next question should start further ahead.
When the information is organized and the context stays with it, people and models can build on what the team already knows instead of starting over.
Why change
You are already paying for AI.
What has that spending delivered for the business? Look at the reports, decisions, and daily work it has changed.
AI spend
What are we getting for it?
Usage tells you how much AI you used. Look at what it helped your team finish.
Measure what gets delivered.
Expertise everywhere
Why are we still starting over?
The knowledge exists across people, systems, files, and conversations, but the next task still starts with gathering it again.
Keep what matters available for the next question.
Prototypes
Why is nobody using it?
The demo worked. It never became part of how anyone does their job.
Check whether people use it in their daily work.
A disciplined approach
Start with one thing that matters.
Start with a slow report, a decision that needs better information, a recurring question, or a prototype your team needs to use.
01 / Command
Pick something worth delivering.
Choose something useful enough to matter and small enough to start now.
02 / Reveal
Organize what it needs.
Bring together the expertise, data, and definitions this task needs, and identify the gaps.
03 / Run
Put it into use.
Use AI and software where they help. Judge it by whether the business can actually use it.
04 / Keep
Keep what you learned.
Save the useful context so the next question starts further ahead.
Finish one useful piece of work and keep what you learned for the next one.
Read: Getting data ready for AI, one dataset at a time“Why can't I just ask Claude?”
You can, and we do.
An answer still needs the right expertise and information behind it. You need to know what the record supports and keep that context after the chat ends.
We help you do that with the tools you already use.
Read: What survives the chat windowWhy CMD+RVL
A little senior help goes a long way.
Your team has experts, data, and probably AI tools already. We help you put them to work on a problem the business needs solved.
Drew and Zac work directly with your team. Two former CTOs, hands-on, helping pick what matters next, organize what it needs, and put it into use.
With a retainer, we stay with your team from one project to the next.
Tie cost to value
Measure what AI delivers.
A report that took two days takes an hour. A check someone ran by hand runs on its own. A recurring question has a standing answer with the sources attached.
Compare those changes with what you spent. That gives you a way to judge whether the AI spending was worth it.
Read: Measure AI by delivery, not tokensCairn
Cairn is our specialist agent.
It runs some of the jobs we build, such as checking a contract for risk or verifying a number against a filing, and it shows its sources.
You can text it for free, or hire it to do the same work across your whole portfolio.
Hire CairnWe have been using the words “quick win” a lot recently but I think what we just witnessed here redefines what a quick win is.
Start with one thing tomorrow.
Bring a report, a recurring task, a decision that needs better information, or an AI experiment you want to put into use. We can organize what that work needs as we go.
Pick something that matters.
Choose something the business already wants.
Organize what it needs.
Bring together only the information and expertise needed to put it into use.
Build from there.
Keep what you learned so the next thing starts further ahead.