Applied AI engineering
AI applications grounded in your data and connected to useful workflows.
I build practical AI features that combine language models with trusted knowledge, tools and product interfaces—focusing on traceable workflows rather than AI added without a purpose.
01 / What you receive
An AI workflow designed around a measurable use case
Grounded answers using your approved knowledge sources
A usable web application with safeguards and feedback paths
02 / Capabilities
What I can build.
- RAG knowledge assistants
- LangGraph agent workflows
- Document search and question answering
- AI interview platforms
- AI-assisted code tools
- LLM API integration and evaluation
03 / Delivery
A practical path from requirement to release.
Define the user task and acceptable failure boundaries
Prepare retrieval, prompts and tool connections
Build the application and evaluation examples
Measure results, latency and operational cost
04 / Relevant toolkit
05 / FAQ
Useful answers before we begin.
What is a RAG application?
Retrieval-augmented generation finds relevant information from an approved knowledge source and supplies it to a model before the answer is produced.
Can AI be added to an existing MERN application?
Yes. An AI service can be integrated behind a controlled API and connected to existing authentication, data and user workflows.
Need this capability for your business?