Twilio

Agent Connect gives an agent a tool system built on standard function calling. A developer defines a name, description and JSON schema, and the SDK formats the tool for whichever LLM provider runs the agent. Custom tools are written with a decorator in Python or defineTool in TypeScript and can read the session, the customer profile and the channel.

Three tools come built in, knowledge search over Enterprise Knowledge, memory retrieval and escalation to a Studio flow that can route into Flex. Because each tool is the customer's own code, the agent can act in any system the customer can reach, and Twilio's own messaging, voice, email and Verify APIs sit alongside as further actions.

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Conversation Orchestrator joins voice calls, SMS and WhatsApp messages into one threaded conversation tied to a customer profile, with a lifecycle that moves each conversation from open to inactive to closed on timeouts the customer sets. Studio, Twilio's visual flow builder, runs multistep communication workflows and receives the agent's handoff payload, and Flex routes the conversation to a person with the history attached. The reasoning inside the agent stays in the customer's own code, while the movement of a conversation between channels, the agent, flows and people runs on Twilio.

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Enterprise Knowledge stores a company's policies, documents and reference material as knowledge bases that agents and human agents search for grounded answers. It is billed as a persistent store, $0.018 per GB hour of storage and $0.005 per retrieval, and Agent Connect exposes it as a knowledge search tool the agent calls when a customer asks a question, returning matching passages for the reply. Customer profiles live separately in Conversation Memory.

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The built in escalation tool hands a conversation to a Studio flow and on to a Flex agent with full context, on voice after the agent's last reply plays and on digital channels by posting straight to the flow. When and why to escalate is the customer's code to decide, and Agent Connect makes no decisions about what the agent does.

Conversation Memory applies a prompt exclusion meant to screen out GDPR special category data. Agent Identity adds scoped, revocable tokens and human approval over SMS or RCS before a high risk action, but it is in private release, so approval before each action is not yet open to every customer.

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Twilio Console sign in works through a corporate identity provider over SAML 2.0, with SP and IdP initiated login and multiple SSO profiles, on Twilio Editions that include single sign on. Which accounts a user can open and which role they hold are set in the Console and Admin Center, and Flex maps identity provider roles to its own.

Twilio holds ISO/IEC 27001 certification and is audited externally on a regular cycle, with security and privacy reports available on request through security.twilio.com. Agent Connect and Conversation Memory are not HIPAA eligible or PCI compliant, so regulated workflows sit outside them.

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Conversation Orchestrator stores every message and transcribed call as a threaded conversation linked to a profile, Conversation Memory shows the observations and summaries it extracted, and Conversation Intelligence analyzes each conversation for sentiment, summaries and custom criteria. Agent Connect logs a warning when it falls back from the Memory API. Together that shows what was said and what the system learned. The tool calls and reasoning live in the customer's agent, so a step by step trace of a run comes from the customer's own logging.

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Conversation Memory keeps one profile per customer inside a memory store. Each profile holds conversational memory, the observations and summaries extracted automatically after each conversation closes, and factual memory, the traits and identifiers that describe the customer. New observations are added, merged with an existing one when they add detail, replace it when they contradict it, or are discarded when they lack support, so the profile stays current.

A Recall API returns the most relevant observations, summaries and recent messages by semantic and lexical search, and Agent Connect calls it on every messaging turn. Up to five stores separate data such as sandbox and production, each profile holds up to 500 observations and 500 summaries, and observations can be switched off per configuration. Memories carry no fixed retention period and persist until they are reconciled, edited or removed.

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The agent and its model run wherever the customer hosts them, since Agent Connect is an SDK inside the customer's own application. Twilio's isolated regions are US1 in the eastern United States, IE1 in Dublin and AU1 in Sydney, and a customer chooses one to keep a workload's data there.

Voice, SIP trunking and messaging run in Dublin, and voice in Sydney, while Conversation Memory, Orchestrator, Enterprise Knowledge and Conversation Relay are offered in the US region only, so the agent layer runs in the US. While regions roll out, Twilio does not guarantee that all data stays in the selected region.

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Agent Connect starts from a quickstart and integration guides for AWS Bedrock and Microsoft Foundry, Conversation Intelligence ships Twilio authored language operators alongside custom ones, and Twilio Skills and the Code Exchange give developers guided patterns and sample apps. Each of these is a starting point the customer builds on. Twilio does not offer finished agents for support, sales or scheduling that a customer switches on.

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Inbound voice calls, SMS, WhatsApp, RCS and web chat all reach the agent through one shared callback, so a single handler serves every channel. Webhooks and WebSocket connections carry the events, and Conversation Relay streams a live phone call to the agent with speech recognition and synthesis handled by Twilio. Outbound sends and calls start from the REST APIs, and Studio flows start on incoming calls, messages or API requests, which covers inbound, event driven and programmatic starts across the channels a contact center uses.

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The customer picks the model. Agent Connect does not run inference. The customer supplies the LLM application and controls how it responds, with integration guides for AWS Bedrock and Microsoft Foundry and support for OpenAI or any other provider. Tools are formatted for whichever provider the customer uses, so switching models is a change in the customer's own code. Twilio's own generative features, such as observation extraction in Conversation Memory, run on models Twilio chooses.

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Every product has a public REST API and helper libraries, including a Conversation Memory API with profile, trait, observation, summary, import and Recall endpoints. Agent Connect itself is an SDK for Python and TypeScript with a FastAPI server for webhooks and WebSockets. An MCP server gives coding agents semantic search across more than 1,500 endpoints in over 30 products, and Twilio Skills package product guidance for AI coding tools.

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Conversation Intelligence runs language operators over voice and messaging conversations, Twilio authored ones for sentiment and summaries and custom ones written as natural language prompts, which a team can point at its AI agent's conversations to flag compliance misses or missed upsells. That reviews live traffic after the fact. The Agent Connect quickstart builds and tests an application locally, and there is no suite of saved test cases with pass or fail results to run against a new version of an agent before it goes live.

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The agent layer connects an agent to communication channels, customer memory and knowledge through APIs and tools the customer writes. No hosted browser, remote desktop or interface control is part of it. An agent that has to work inside a web page or a desktop application brings that capability as a custom tool in the customer's own code, outside anything Twilio runs.

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