Danny kaganovitch

You don't need the app rebuilt — you need AI inside it, working properly, without breaking what already works. I read the existing codebase first, then add the AI layer where it belongs.

Retrieval-augmented agents on a proper backend: your content indexed into a vector database, retrieval tuned so answers cite real sources, and tool access so the agent can do things rather than only reply.

Model Context Protocol is how AI assistants reach real systems — your database, your CRM, your internal APIs. An MCP server is an API design problem with an AI consumer, which is exactly the work I've done for a decade.

Revenue operations usually span three systems that don't talk to each other. I build the tool layer that lets one agent query and act across all of them, with the audit trail finance needs.

Production APIs, a real database schema, auth, tests and a deployment that holds up. This is the foundation that keeps AI projects from stalling at the demo stage.