Development services
AI-assisted development
Use AI-assisted tools to accelerate exploration while retaining engineering review and ownership.
Intelligence with connected context
01 / The detail
What we can build
Use AI-assisted tools to accelerate exploration while retaining engineering review and ownership.
- Prototype assessment
- Repository and test setup
- Human code review
- Production readiness work
02 / The detail
Illustrative use case
An AI-generated prototype is reviewed, connected to real authentication and prepared for controlled deployment.
03 / The detail
Decisions that matter
Generated code needs the same security, licensing, accessibility and reliability checks as other code. Exportability and maintainability matter beyond the demo.
04 / The detail
From scope to a working release
Begin with the people, systems and decisions involved in this workflow. Agree what a useful first release must do, then validate its most uncertain dependency before expanding the build.
- A scoped workflow and explicit acceptance criteria
- A tested implementation with documented dependencies
- Deployment, recovery and maintenance responsibilities agreed before handover
Delivery, end to end
A clear path through the build.
Discover the right problem
Understand users, existing systems and constraints. Define the outcome, acceptance criteria and dependencies before committing to a delivery scope.
Design and validate
Map the workflow, prototype key interactions and test the highest-risk technical assumptions. Agree the architecture and the first useful release.
Build in useful increments
Implement working slices with code review, meaningful tests and regular demonstrations. Review access controls, failure states and operational requirements as part of delivery.
Release and keep improving
Verify deployment and recovery, document ownership and hand over operation. Use feedback and observed behavior to prioritize support and the next iteration.
Questions, answered
Before we begin.
When is AI-assisted development a useful fit?
Use AI-assisted tools to accelerate exploration while retaining engineering review and ownership. Start by comparing the required workflow with your existing systems. An AI-generated prototype is reviewed, connected to real authentication and prepared for controlled deployment.
What should we resolve before implementation?
Generated code needs the same security, licensing, accessibility and reliability checks as other code. Exportability and maintainability matter beyond the demo.
How do we begin a project?
Share the workflow, intended users, existing systems and any release constraints. Discovery establishes scope, dependencies and acceptance criteria; estimates follow that assessment rather than a fixed promise before the requirements are known.
Keep exploring
Connected capabilities.
Cursor AI development & integration
Use repository-aware coding assistance within an accountable engineering workflow.
Lovable AI development & integration
Assess and extend a Lovable-built prototype into a maintainable application.
Product engineering
Move from a product hypothesis to a usable release, then improve it using evidence from real workflows.
Start with the problem.
Build the right solution.
Bring your idea, workflow or existing application. We’ll help define a practical next step.