How we build agents that survive production.

We start by listening.

We find out what's actually breaking, and whether AI is even the right answer. Sometimes it isn't, and we'll tell you. If a tool you already pay for can do it, we'll say so.

• What you're trying to do
• Where it breaks today
• Whether an agent is the fix

You leave with Whether AI fits, and what it would cost.

We design before we build.

A lot of what goes wrong is decided before any code exists, and that's the cheapest place to catch it.

• What the agents do
• What data they touch
• Where people stay involved
• How it fails

You leave with Architecture, data map and failure plan, in writing.

Built around your business.

Custom code written for how you work, with error handling and logging from day one, tested against your industry's edge cases before a customer meets it.

• Custom code
• Error handling from day one
• Logging at every critical step
• Tested on your edge cases

You leave with Working code, tests and readable logs.

We stay until it's running.

We watch it live, fix what surfaces, and hand over once it's steady.

• Live monitoring
• Fixes as they surface
• Handover to your team

You leave with The repository, the docs, and a team that can run it.

What those two weeks are actually for: running the old process and the agent side by side until they stop disagreeing. It is the step that catches what a demo structurally cannot.