Services
Find the right AI work, then build it into your workflow or product.
We can assess an opportunity, guide delivery, build an agent, or add AI to your product.
AI opportunity and readiness
We map a real workflow, assess its constraints, and rank AI opportunities by value and feasibility.
Typical work
And then
OutcomeA prioritized opportunity map and a practical recommendation for what to build first.
Fractional AI CTO
An embedded partner for AI priorities, technical decisions, and delivery with your existing team.
We help with
And
OutcomeA decision maker and delivery partner for your AI initiatives.
AI agent and workflow implementation
We build agents around your existing tools, data, and people, with human review where the work requires it.
Examples
And
workflow analysisagent designintegrationevaluationhuman reviewdeploymentimprovement
OutcomeA working agent integrated into an agreed workflow, with a way to review its output.
AI-native product engineering
We combine product thinking and AI engineering to design, build, and evaluate capabilities for your users.
This may include
And
OutcomeAn AI product capability designed around a clear user task and tested for quality.
How we work
Is the opportunity worth pursuing?
Are the workflow, data, systems, and organization ready?
Can the system be trusted in the real environment?
Will people use it effectively in the workflow?
Can successful capability become part of the business?
Who we work with
Start with the business problem. We can work backward from there.
You may be a good fit if:
Frequently asked
Start with one workflow or product problem. We can assess its value, data, risks, owner, and a practical first step before proposing a build.
Yes. We build AI agents for internal workflows and AI capabilities inside customer-facing products.
Yes. We define responsibilities with your CTO, CIO, product, and engineering leaders at the start.
Not always. The answer depends on the workflow and its data needs. We assess access, quality, and integration before deciding what to build.
It depends on scope, integration, risk, and review requirements. We agree on milestones after understanding the workflow.
Controls are designed for the use case and may include access limits, test cases, human review, monitoring, and escalation paths.
Insights
The constraints an established business arrives with — the process, the systems, the exceptions nobody wrote down — are not obstacles between you and the AI. They are the specification for it.
A pilot proves a model can do something. Production proves an organization can rely on it. The gap between the two is not technical, and it is where most programmes stop.
The usual selection method produces forty ideas scored on two axes nobody can estimate before building. Four questions predict a first workflow better, and every one of them is answerable in a week.
Next step
Tell us about a workflow or product you want to improve. We will help you find a useful next step.
No AI solution needs to be defined before we speak.