Agentic AI & Retrieval Systems (Multi-Agent RAG & MCP)
Architect and deploy autonomous agentic systems and multi-agent RAG — from Model Context Protocol (MCP) server integration to production edge-first configurations.
Service Overview
If your team has already tried a basic RAG implementation and hit a wall — stale retrieval, hallucinated citations, agents that don't know when to defer — this is the next layer: production-grade, multi-agent retrieval architecture built for real enterprise data. As an Agentic AI Engineer and MCP integration specialist, I design reliable agent workflows that plan, tool-call, verify, and execute securely across your private data ecosystem.
What's Included
- multi-agent architecture design
- Model Context Protocol (MCP) server & client integration
- retrieval pipeline engineering
- evaluation framework
- and production deployment support (including edge-first configurations where data can't leave the device).
Tools & Technologies
Frequently Asked Questions
What is the Model Context Protocol (MCP) and how do you use it?
Model Context Protocol (MCP) is an open standard connecting AI models to external tools and data sources safely. We design and build custom MCP servers and client integrations that allow your agents to securely inspect databases, query enterprise APIs, and run local utilities without exposing raw credentials or sensitive data.
What's the difference between RAG and agentic RAG?
Standard RAG retrieves and answers in one pass. Agentic RAG adds decision-making — the system can re-query, verify, call external tools via MCP, or route to a specialized sub-agent when the first retrieval isn't good enough.
Can this run without sending data to a third-party API?
Yes — on-device and edge-first configurations are part of the offering, specifically for teams that can't send data externally.
Do you build on existing vector DB infrastructure or start from scratch?
Either — most engagements start with an audit of what you already have.
Who is this for?
- You want an Agentic AI Engineer who can design multi-agent handoff logic and reliable tool-calling execution, not just single-shot retrieval
- You need an MCP Integration Specialist to implement Model Context Protocol servers connecting internal databases and APIs to frontier LLMs
- Your RAG implementation works in testing but breaks down on real document volume or query complexity
- You need an AI Agent Developer for US, UK/EU, or Australian enterprise deployments with strict reliability guarantees