Practical AI for Software and Development
Microtechnics helps companies introduce practical AI into existing software systems and development workflows — from AI-assisted engineering to LLM integrations, internal tools and agents.
Start with a defined pilot
The objective is not to install another tool. It is to integrate AI into real engineering work while maintaining appropriate permissions, review, testing and technical boundaries.
Introduce AI-assisted workflows into existing repositories: codebase analysis, implementation, testing, debugging, refactoring and documentation. Includes repository instructions, permissions, validation, MCP and development-tool integration.
Add practical AI capabilities to existing business applications through LLM APIs, agents, internal tools, structured data access and controlled process automation.
Typical pilot scope
Deliverable: A working AI solution or engineering workflow validated against agreed use cases, with documented technical boundaries and recommendations for further rollout.
How the pilot works
Understand the codebase, development process and target use cases.
Select a specific use case, technical scope and measurable pilot criteria.
Configure instructions, permissions, workflows and integrations.
Validate changes through existing build, test and review processes.
Document the workflow and define practical rollout steps.
