AI That Does Real Work.
We build AI features and workflow automation into your product or operations, scoped to a specific job and tested like every other part of the system.
Demos are easy.
Production is not.
A lot of AI projects start as a chatbot bolted onto a website. It answers confidently, sometimes wrongly, and nobody can tell whether it's actually helping anyone.
Meanwhile the useful work goes untouched: sorting inquiries, drafting replies, pulling details out of documents, moving data between tools. Teams know a model could handle some of it, but not where to start or how to keep it safe.
One job at a time.
Tested like software.
We start with one clearly defined task and a way to measure whether the model does it well. Then we build it into your app or workflow with the Claude API or the OpenAI API, sending the model only the data that task needs.
We build with AI every day. Our own engineering runs on Claude Code with MCP tooling, so we know where models are strong and where they need guardrails. A human engineer reviews and owns everything that ships.
James's QA automation background (more than three years, including ServiceNow) shapes how we test: a set of real example inputs with expected results, checks we rerun whenever the prompt or model changes, and human review wherever a wrong answer would cost you.
- Claude API and OpenAI API integrations
- Answers grounded in your own documents and data
- Workflow automation connected to the tools your team already uses
- Test sets and guardrails before launch
- Firebase or Node.js backends to run it
From idea
to working feature.
Pick the job
We choose one task worth automating and agree what a good result looks like.
Prototype on real examples
A quick build tested against your actual inputs, so you see real results, not a demo script.
Build it in
The feature goes into your app or workflow with logging, limits and a fallback when the model isn't sure.
Test & launch
The test set runs before every release, and people review the high-stakes steps.
Monitor & improve
We track how it performs in real use and tune prompts, data and models as needed.
AI questions,
straight answers.
Which AI models do you work with?
Mainly Anthropic's Claude API and OpenAI's API. We choose per task based on quality, speed and cost, and keep the model behind a thin layer in your code, so switching later doesn't mean a rewrite.
Will our data be used to train AI models?
We use the providers' business APIs, whose terms say API data isn't used to train their models by default, and we send only the data a task needs. We'll go through the provider's current data terms with you before anything goes live, with the Data Privacy Act of 2012 in mind.
What happens when the AI gets something wrong?
Sometimes it will, so we design for it: tests on real examples before launch, checks on the model's output, a human review step wherever a mistake would be costly, and logs so problems can be traced and fixed.
Can you add AI to an app we already have?
Usually, yes. Most AI features sit in your existing backend or in a small service beside it. We review your codebase first and tell you the simplest way to add it.
Keep exploring.
Book a free
20-min discovery call
Tell us what you're building. You'll talk to James directly, get an honest read on scope, and leave with next steps, whether or not we work together.