Twilio unifies AI and human conversations with new layer
▼ Summary
– Twilio announced three new components at SIGNAL 2026—Conversation Memory, Conversation Orchestrator, and Conversation Intelligence—to create a persistent, continuous customer experience across channels and agents.
– Conversation Memory builds an ongoing, identity-resolved profile combining customer data with interaction history, allowing agents to pick up where the last interaction left off.
– Conversation Orchestrator manages the flow of interactions across channels and handoffs between AI and human agents, stitching individual touchpoints into a single thread.
– Conversation Intelligence analyzes live interactions in real time for signals like sentiment and escalation risk, triggering actions during the conversation.
– Twilio also introduced Agent Connect for model-agnostic AI integration, expanded channel support (Apple Messages for Business, Twilio Email), and updated voice AI features.
Twilio has unveiled a new suite of platform features designed to solve a fundamental frustration in customer experience: conversations that fail to carry context across different touchpoints. The announcement, made today at SIGNAL 2026, introduces three core components that form what the company calls a new “conversation layer,” uniting data, channels, and both human and AI agents into a seamless, continuous interaction.
The logic is simple. Too many customer journeys remain disjointed. A user may start with a chat, shift to a phone call, and then follow up via email, often repeating the same information at each stage. This fragmentation hurts conversion rates, customer retention, and operational efficiency. Twilio’s approach treats conversations as a persistent thread rather than a series of isolated events.
The three new components are designed to ensure that every interaction begins with context, maintains state, and can adapt in real time. Conversation Memory builds an ongoing, identity-resolved profile that merges customer data with past interactions. This allows both human agents and AI systems to pick up seamlessly where the last exchange ended, eliminating the need for customers to start over. Conversation Orchestrator manages the flow across channels, handling handoffs between AI and human agents to stitch individual touchpoints into a single, cohesive journey. Conversation Intelligence adds a real-time analytical layer, monitoring live interactions for signals like sentiment shifts or escalation risks, and triggering actions while the conversation is still active.
Twilio believes this will help companies shift from reactive engagement to something more like continuous interaction. That reflects a broader industry shift: the question is no longer whether AI can respond to customers, but whether it has enough context to respond well. Twilio argues that the real bottleneck isn’t the AI model itself. It’s the infrastructure that connects everything around it.
The company is also emphasizing flexibility. With Agent Connect, developers can plug in different AI models or frameworks without rebuilding their communications layer. The platform remains model-agnostic, giving teams more control over how they deploy AI while avoiding vendor lock-in.
Beyond the core conversation layer, Twilio is expanding its channel and platform capabilities. New support for Apple Messages for Business is now available, along with general availability of Twilio Email. Updates to voice AI features include real-time transcription and smarter turn detection. A redesigned console aims to simplify how teams manage increasingly complex engagement stacks, with unified logs, billing, and an embedded assistant.
Early customer examples highlight practical applications. Companies are using the platform to recover stalled applications, guide live conversations with real-time data, and reduce the need for repeated manual follow-ups. The common thread in each case is continuity: carrying context forward rather than restarting from scratch.
(Source: MarTech)
