Architecture Overview

Every Guava call involves two systems running simultaneously: Guava's hosted Dialog System and your Expert — a small, long-running service that connects to Guava's API and steers the conversation.

The Dialog System

The Dialog System is Guava's managed service running in the cloud. It handles everything time-sensitive during a call: receiving the caller's audio, running speech-to-text, querying the language model, synthesizing the response, and streaming it back to the caller.

Because the entire pipeline runs as a fully integrated architecture rather than a chain of off-the-shelf APIs, the Dialog System delivers best-in-class latency and naturalness. Callers hear a response that feels like a real conversation, not a chatbot reading from a script.

Your Expert

Your Expert is the code you write. Using the Guava SDK (Python or TypeScript), it connects to the Dialog System over a persistent WebSocket and steers the agent in real time — setting its persona, sending mid-call instructions, responding to events like on_question or on_action, and issuing commands like transfer or hangup.

Because your Expert is just code, you can do anything: call your CRM, query a database, hit an external API, or chain into another specialized AI sub-agent. For the most common patterns — intent detection, document Q&A, vector search — Guava ships a helper library so you can get up and running fast without reinventing the wheel.

During development, your Expert runs on your local machine, and Guava routes calls to it directly. You can rapidly iterate by changing the code and restarting the process — no public web server or ngrok required.

Deployment

When it's time to move to production, you'll want your Expert deployed in a highly-available configuration, running continuously and ready to handle calls at any time. Because Guava Experts only make outbound connections, it's easy to run an Expert behind a NAT or firewall.

We recommend running multiple instances of the same Expert. Guava round-robins new calls across connected Experts, giving you horizontal scaling and redundancy by default. If an Expert instance dies mid-call, Guava will attempt to hand the call off to another active instance — which means you should keep in-memory state to a minimum and design your Expert to be stateless where possible.

You have two options for deploying your Expert:

• Your Infrastructure — deploy to your own servers, VM, or serverless compute platform. You control the environment.
• Guava Hosting — push your Expert with a single guava deploy command and Guava manages the rest.

See the Deployment guide for a full walkthrough of both options.

What to read next

The Quickstart walks you through a complete working example in minutes. Once you're comfortable with the basics, the SDK Reference covers every callback and call command in detail. If you want to see a real-world use case before diving into reference docs, the example walkthroughs show full Expert implementations for common scenarios.