Services
AI / LLM
LLM and RAG Application Strategy
Designing AI systems that use retrieval-augmented generation to answer questions from trusted business knowledge and operational data.
How I help
I help teams plan RAG systems around knowledge source quality, document ingestion, metadata, retrieval design, prompt strategy, and evaluation so LLM responses are grounded in trusted business context.
Outcomes
- Better answers from trusted internal knowledge
- Reduced hallucination risk through retrieval design
- Clearer knowledge architecture before implementation
- Support workflows that fit how teams actually work
Deliverables
- RAG architecture plan
- Knowledge source inventory
- Retrieval strategy
- Prompt framework
- Evaluation checklist
Tools and platforms
- OpenAI
- Anthropic Claude
- Google Gemini
- Embeddings
- Vector Search
Best fit
- Teams building internal support assistants
- Organizations with scattered documentation
- Support teams that need trusted-answer workflows
Contact
Want to discuss AI, data, or Salesforce architecture?
I’m open to consulting, technical advisory, architecture reviews, and relevant professional opportunities.