Twilio is rolling out a new set of platform capabilities to address one of the most persistent problems in customer experience: conversations that don’t carry over from one interaction to the next.
Announced today at SIGNAL 2026, the three new components are a new “conversation layer” designed to connect data, channels, and both human and AI agents into a single, continuous experience.
The premise is straightforward. Most customer journeys are still fragmented. A user might start in chat, move to voice, then follow up via email, repeating information at every step. That disconnect affects conversion, retention, and operational efficiency.
Twilio’s answer is to treat conversations as a persistent system rather than a series of disconnected events.
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Carrying context forward
That’s where its three new core components come in. Conversation Memory, Conversation Orchestrator, and Conversation Intelligence aim to ensure that every interaction starts with context, carries forward state, and can adapt in real time.
- Conversation Memory creates an ongoing, identity-resolved profile that combines customer data with interaction history. Instead of treating each engagement as a fresh start, it allows both human agents and AI systems to pick up exactly where the last interaction left off.
- Conversation Orchestrator handles the flow. It connects interactions across channels and manages handoffs between AI and human agents, effectively stitching individual touchpoints into a single thread.
- Conversation Intelligence adds a real-time layer, analyzing live interactions for signals such as sentiment and escalation risk, and triggering actions while the conversation is still happening.
The company hopes this will let companies move from reactive engagement to something closer to continuous interaction.
That shift reflects a broader change in how companies are thinking about AI in customer experience. The issue is no longer whether AI can respond to customers, but whether it has enough context to respond well. Twilio’s framing is that the real bottleneck isn’t the model. It’s the infrastructure that connects everything around it.
More new features
The company is also leaning into 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 greater control over how they deploy AI while avoiding lock-in.
Beyond the core conversation layer, Twilio is expanding its channel and platform capabilities. That includes new support for Apple Messages for Business, general availability of Twilio Email, and updates to voice AI features like real-time transcription and smarter turn detection.
There’s also a redesigned console intended to simplify how teams manage increasingly complex engagement stacks, with unified logs, billing, and an embedded assistant.
Early customer examples point to practical use cases. 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. In each case, the common thread is continuity: carrying context forward rather than restarting from scratch.
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