Guides

The term "AI agent" is everywhere right now. But what actually is an agent? And what makes it different from a chatbot or a standard AI assistant?

A single patient encounter can touch clinical documentation, billing codes, scheduling systems, formulary checks, and clinical guidelines. Trying to handle all of that with one LLM is a recipe for mediocre results.

Build it yourself or buy a pre-built solution? Both have real drawbacks. There is a third path worth considering.

Building an agent is easy.. Running it in production alongside other agents, and serving users, with healthcare-grade compliance, is a different problem entirely.

Corti Agentic Framework is built on A2A and MCP, two industry standards that ensure interoperability and reduce lock-in.

To avoid rebuilding the same healthcare AI basics, Corti’s expert registry delivers pre-built experts for clinical references, coding, drug interactions, and literature search.

If you give a single LLM too many tools, that's where limitations arise. It may pick the wrong tool, forget context more often, or simply mess up the overall workflow. This is an architectural limitation.