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Add practical AI capabilities to your product
I help companies integrate AI features that work inside real products and workflows — not demos that never ship. From RAG-powered search to intelligent assistants, the focus is always on reliability and business value.
Common challenges
- You want to add AI to your product but aren't sure where to start
- Your team built a prototype but can't get it to production quality
- You need AI features that work reliably with your existing data
- You're evaluating build vs. buy for AI capabilities
What you get
- AI feature architecture and implementation plan
- RAG pipeline design and deployment
- AI assistant or agent integration
- Evaluation framework and quality guardrails
- Production deployment and monitoring setup
Examples
AI-powered search
Semantic search across product data, documentation, or knowledge bases.
Document intelligence
Extract, classify, and summarize information from unstructured documents.
AI assistants
Context-aware assistants embedded in your product workflow.
AI agents
Autonomous agents that complete multi-step tasks with human oversight.
How I approach it
- 01Start with the business problem, not the technology
- 02Design for reliability with evaluation and guardrails from day one
- 03Build incrementally — ship a useful v1, then iterate
- 04Integrate with existing systems rather than replacing them