Damon M.

I help enterprise and mid-market teams put AI into production where wrong answers are expensive: grounded RAG, knowledge graphs, and natural-language-to-SQL that return verified, auditable results instead of plausible guesses. I'm Co-Founder and Chief Growth Officer of DaaX, an enterprise AI company named an IDC Innovator in Context Infrastructure for Agentic AI (2026). I scope, architect, and lead each engagement; delivery is done with DaaX's engineering team, which built the platforms below. What we deliver • Grounded RAG and hallucination reduction. Our LAKEer platform scored 77.7% grounding accuracy on Google DeepMind's FACTS benchmark using GPT-4o mini, above the previous best of 74.3% by Gemini 2.5 Pro. • Natural language to SQL. Our SQLer engine reached 95% hand-crafted SQL quality vs. ~60% for generic LLM approaches in a Fortune 500 customer benchmark. SQL Server, MySQL, PostgreSQL, and Oracle. • Knowledge graphs and ontologies. Typed knowledge graphs, OWL ontologies, SPARQL, and domain vocabularies, including OSDU for oil and gas and FIBO for financial services. • Enterprise search and AI agents. Multi-channel semantic and graph retrieval, plus MCP servers that give agents verified knowledge with source provenance. • Unstructured "dark data." Turning PDFs, reports, and complex tables into queryable, verified intelligence. How we work Fixed-price, milestone-based engagements with a clear definition of done. Every answer the system produces is traceable to its source. Background: B.S. in Electrical Engineering, Cornell; MBA, Wharton. 25+ years in enterprise technology, GTM, and technical sales across financial services, defense, healthcare, and e-commerce. If your AI works in the demo but not in production, send me the use case and I'll tell you honestly whether we can fix it.