Expertise
We build AI agents and automation that run in production.
Agents, an AI-ready data layer, readiness audits, team training, and AI inside your automations, built with Claude and kept running as the models change.
Position
Most of the work in an AI build is the data, orchestration, and controls around the model.
Building an AI agent is now quick. The tools and models are good enough that the gap between an idea and a working agent is small.
The harder questions are around the agent: how to structure your data so a model can use it, how to orchestrate several agents, when to keep a person in the loop, how to raise accuracy without raising cost, what your company's Claude strategy should be, and what skill files your team needs. We have spent the last two years answering those questions for ourselves and for our clients.
What we build
Five things we build and run for you.
- AI agentsAgents with tool use, MCP integration, multi-agent orchestration, evaluation, and observability, built on the Claude Agent SDK and run in production. A single agent for one task, or several coordinated when the work spans your operations.
- AI-ready data layerYour company's data structured so a model can use it: clean inputs, governed access, and an architecture that holds up as you add use cases.
- AI audits and readinessAn assessment of where AI pays off in your business today, where it will once the data foundation is in place, and where it will not, so you spend on the first group.
- AI trainingHands-on sessions for your team on prompt design, the tools, and how to put AI into their own workflows.
- AI-assisted automationRouting, content generation, classification, and extraction handled by a model as a step inside your existing Make, n8n, or custom-code automations.
Our approach
Three steps from audit to production.
- Step 1
Assess
We audit your operations, your data, and your team's readiness, then list where AI fits and in what order.
- Step 2
Build
We design, build, and deploy the agents, data layer, and AI-assisted workflows, wired into the systems your team already uses.
- Step 3
Run
We train your team, document the work, and stay on to tune it as the models and your processes change.
Proof
What a client says about running his business with Claude.
I've worked with Keenan and the Workiflow team for over two years, and what stands out most is how they adapt as fast as the technology does — by the time we were ready for Claude, they were already ahead of us. They built the governance first, which is the only reason I was comfortable putting this in front of my team, and then showed us what it could really do: connectors into the systems we already run, and projects and skills built around our actual work, not a demo.
The difference between running my business with Claude and without it is like the difference between working with electricity and without it.
I came into this with almost no development experience, and a few weeks later I had written the requirements for, built, and merged a working feature myself with Claude Code. The work it takes off my plate every week is easily 80 hours' worth, and that's before the rest of the team hits their stride.
It's been a genuine pleasure working with Keenan and his team, and I'm looking forward to a long relationship as we keep growing the business.
Next step
Book a discovery call.
Tell us where you want AI to take work off your team. You leave the call with a view on what is ready to build now, what needs the data fixed first, and whether it is a project or a retainer.
30 minutes. No commitment.