Bring one business outcome. Leave with a working system.
Bring us one workflow you want to make faster, or one software initiative you need to ship. We turn it into a production-grade AI system built around your tools, your constraints, and your KPIs.
The goal is not training. The goal is a working system with the architecture, governance, testing, release path, and operating model required to move forward.
App, or workflow? The sprint goes one of two ways.
Some outcomes need real software, built faster with coding agents. Others should never become apps at all. They should become governed AI workflows that run inside the tools your business already uses. The first thing we do is help you make that call: app, workflow, hybrid, or don’t build.
Workflow Factory
Use agents to do the work.
We turn one recurring, high-friction process into a governed agent: mapped to your real steps, wired to your systems, tested against your real history, with humans in review where judgment matters.
Software Factory
Use agents to build the software.
We stand up the AI-native way of shipping software around your real repo: coding harness, repo instructions, automated tests, AI code review, and release checks that decide what’s safe to ship.
Not sure which? We help you decide first. No strings.
We find where agents create leverage.
Whatever the outcome, a workflow or an app, we start the same way: map the current state, find the leverage, then install the factory around it. Here’s a real one of each (anonymized).
An auto-warranty claims workflow: high volume, repetitive, run by hand across several systems.
In the sprint we build that agent against your real workflow: the adjuster stays on judgment, the agent takes the toil, and you leave with it running.