01
Repository context and guidance
Organize project instructions, architecture notes, setup steps and task boundaries so AI-assisted work starts with the relevant context.
AI development workflows
Make AI useful in your team’s development workflow.
Help your engineers use AI for a specific development task, with the project instructions, code review and tests it needs. We start with one repository and measure the work your team actually accepts.
Discuss an AI development pilot Concept illustration
Where we help
Choose where AI should help your engineers.
We set up AI-assisted development around your codebase and existing review process. Your engineers receive project guidance, example tasks and a way to assess the results before adopting it more widely.
02
Implementation and review workflows
Define suitable tasks, branch and review practices, and the checks needed before generated changes are accepted.
03
Testing and delivery checks
Connect useful tests and CI checks to the workflow. Assess application behavior, regressions and review effort alongside implementation.
04
Try it on a real development task
Try AI on one development task, then review the time spent, corrections needed, quality of the accepted work and cost. Document what the team needs to use it again.
A practical starting point
One working setup, tested on your team’s tasks.
A working pilot and a documented evaluation give your team evidence for deciding whether to adopt, change or expand the workflow.
Why Stax3
Engineering context throughout
We connect AI use to architecture, implementation, testing and delivery decisions, with engineers responsible for reviewing the work.
Instructions your team can keep using
Your team receives setup instructions, checks and clear responsibilities so it can keep using and maintaining the workflow.
Engineering decisions
Start small, evaluate the work, then expand.
Review the existing workflow
We map the repository, tools, task types and current checks. Together we select a useful pilot and define what improvement would mean.
Set up a controlled pilot
We prepare context and instructions, define access and review boundaries, and implement the selected workflow with representative tasks.
Evaluate and hand over
We review output quality, rework, time and operating cost with your team. You receive workflow documentation and recommendations for the next step.
First deliverable
A pilot your engineers can assess.
The first engagement produces a configured workflow, representative tasks, agreed checks and an evaluation summary. We define success with your team and report what the pilot demonstrates, including the limits.
Explore AI product and business workflowsUseful answers
Before we start.
Is this the same as adding AI to our application?
This service improves how your team develops software. Our AI product and automation service covers features and operational workflows used by customers or staff.
Can you review an AI-built prototype?
Yes. We can review the actual code, authentication, data handling, tests and deployment, then define a staged improvement plan. Implementation is estimated from the findings.
Will AI make our developers faster?
The effect depends on the tasks, codebase and review process. We evaluate accepted work, rework, quality and cost in your pilot instead of promising a fixed speed increase.
Start with the context
Which development task should work better?
Tell us about your repository, current tools and the task you want to improve. We will help define a pilot and how to assess it.
Discuss an AI development pilot