Make the case internally.

One of three things, depending on how much you already know. If one recurring job is the problem, a done-for-you agent: $12,500 fixed, live in as little as three weeks. If the problem is clear but the fix isn’t, an AI Jumpstart: fixed scope and fixed price, two to eight weeks, ending in software you can click through and a plan for what to build in what order. If you already know what to build, the AI Deployment Studio builds it with you, as a project or a monthly retainer.

We size the work to the problem, not the budget, and won’t push you toward a bigger engagement than the problem calls for.

Go deeperThree ways to start

With one job, not a whole program. The best first pick is work with volume and rules: it arrives every day and gets handled the same way. If it isn’t clear which job that is, the Jumpstart works it out with you: we map how the work actually moves, rank where AI pays off, and prototype the first one on your real workflows.

For a head start before any call, the free assessment takes six minutes, needs no email, and you keep the map.

Go deeperFind your AI opportunities

Each step stands on its own, so you only commit to the next one once the last one has shown what it can do. An agent is tested on your own past work before it goes live, then runs beside your team with every output checked. A Jumpstart ends with a working prototype and a plan that are yours whether or not we build it together. You can take them to your team, to someone else, or wait until you’re ready.

Chat assistants like ChatGPT and Copilot help one person at a time. Tools like Zapier move data from one system to another on a rule. An agent works behind your team on a whole job: it reads what comes in, checks it against your systems and rules, does the work, and hands the odd case to the right person, who signs off. It works on the same records your people use, so everyone sees one version of the work.

If the tools you already have can do the job, we’ll tell you.

The patterns repeat across industries: work comes in, gets checked, gets approved and gets reported. We’ve built for a cargo surveying firm, a specialty lender, a commercial real estate firm, an insurance carrier and a SaaS company, among others, and the results below link to each case. Because our own delivery runs on AI, we get fluent in what’s specific to your business in weeks, not quarters.

Mostly the hires you’ll make instead. When volume grows, the default fix is adding people to do the same manual work, rather than building a system that grows your team’s capacity.

We ship working software in weeks, not a strategy deck after months. One team maps the work, builds it and rolls it out. If you’re planning an AI hire, we can build the first system and hand it over to them.

That’s planned from the start, not hoped for at the end. We build with the people who do the work, around how they already work, and the same team that built it runs the rollout: a pilot group on real workflows first, then wider. For the first 30 days after launch, anything that gets in the team’s way is treated as product work to fix, not a training problem.

If people don’t adopt it, that tells us we built the wrong thing.

It’s a fair question, and the people asking it should get a straight answer. How roles change is your call, not ours. What we control is how it’s built: with the people who do the work, so the system takes the copy-paste and leaves them the judgment calls. At one client, a PE group running three equipment manufacturers, nobody lost a job.

It’s agreed up front. For an agent, someone who does the job today needs about an hour a week, and your team gives us secure access; we do the connecting. For a Jumpstart or a build, it’s usually two or three people from your side: whoever owns the workflow and the people who run it.

Three people from our side stay with it the whole way: a project manager, a business systems strategist and an engineer. The project manager runs a weekly check-in with your main stakeholder.

The judgment calls. Approvals, exceptions, and anything that needs a documented reason stay with your team, and the system enforces that instead of letting it get bypassed on a busy day. AI carries the reading, routing and assembling around the decision, so the person making it starts with the full picture.

We stay close. An agent keeps being tuned for 30 days after it goes live. A Studio build stays through rollout, training and the first weeks of real use, and you can keep us on for the next piece of work if and when it helps. Either way, the code, the accounts and the documentation are yours, and what we ship is built to be run by an operations team.

Some teams can, and we’ll tell you when that’s the right answer. A prompt in a chat window is single-player. A system that runs in the middle of a live business is different: real data, integrations, and the cases nobody documented. A demo on the textbook case is the easy part, and most of the work is in the exceptions, which is where pilots tend to stall. That’s where we start, and we stay until it’s in production.

AI writes much of the first draft. Senior engineers review it, and nothing ships without their sign-off. We use AI where it helps, and we say so when it doesn’t.

Your records stay in your systems. Each step sends the AI only what that step needs to read, through a secure business account that belongs to your company. The providers we work with, like Anthropic, OpenAI and Google, hold the major security certifications, and their business accounts don’t train on your data.

You get the data flow in writing before we connect anything, we work through your vendor and security review with you, and our team gets only the access the build needs, handed back at handover.

Usually, and without a migration. Most of what we build connects the systems you already have, and older or homegrown systems are normal. Replacement is an outcome, not the starting plan: if mapping the work shows a tool should go, we’ll say so. In a Jumpstart, the system and data audit shows where the gaps are before anything new is built.

You do, free and clear. It runs in your cloud and your tools, on an AI account in your company’s name, and the code is handed over with the runbook. Every automated action carries an actor, a timestamp and a reason, captured as the work happens, so when someone asks why something happened, the answer is a lookup, not an investigation.

Before go-live it’s tested on your own past work, so we know where it’s reliable. Anything it’s unsure about goes to an actual person instead of slipping through. After launch, every miss becomes a new test, so it doesn’t make the same mistake twice.

It depends on the way in, and each one is priced before you start. A done-for-you agent is $12,500 fixed, with no license fees. A Jumpstart is fixed scope and fixed price, quoted after a first call. A Studio build runs as a project or a monthly retainer, sized from the Jumpstart’s plan.

Once an agent is live, hosting and AI are paid straight to the providers, not through us, and we work out that figure from your real volumes before you sign.

We measure where you are before any work starts. For an agent, we agree the number on the first call and measure it again at day 30, so you can see what changed. A Jumpstart puts the time and cost savings against your current state on a working prototype, before any larger build. If the numbers don’t justify the next phase, you stop there.

You’ll know before you pay in full. An agent is billed half at kickoff and half when it goes live. Before that, it’s tested on your own past work, and if that shows it can’t do the job the way you need, we stop there and you don’t pay the second half.

Yes. The default path is a Jumpstart first, mapping and a prototype, then the AI Deployment Studio for the full build. You can stop after the Jumpstart. You can pause between phases. You can run several Jumpstarts before any build. You decide based on what you have learned by then.

And if one job is already clear, a single done-for-you agent at a fixed price is the smallest first step. Its fee counts toward a Jumpstart or Studio engagement signed within 90 days.

None. You own the source code, the documentation and the system access. There’s no recurring license fee and no platform you keep paying for. If you want to bring it in-house, you can.

That math flipped. SaaS used to be the safe choice because building was slow and expensive. AI changed the cost of building, and your stack of 5 to 10 tools still doesn’t fit how you run. What took five developers eighteen months in 2006 now takes two developers about four, and you own the result. Custom is becoming the conservative choice.