Twilio is rolling out a new set of platform features to solve one of the most persistent problems in customer experience: conversations that don’t flow from one interaction to the next.
Announced today at SIGNAL 2026, the three new components constitute a new “conversation layer” designed to connect data, channels, and human and AI agents into a single, seamless experience.
The principle is simple. Most customer journeys are still fragmented. A user can start by chatting, move to voice, and then follow up with email, repeating the information at each step. This 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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Advancing the context
This is where its three new main components come into play. Conversation Memory, Conversation Orchestrator, and Conversation Intelligence aim to ensure that every interaction starts with context, continues with state, and can adapt in real time.
- Conversation Memory creates a continuous, identity-resolved profile that combines customer data with interaction history. Instead of treating each engagement as a fresh start, this allows human agents and AI systems to pick up exactly where the last interaction left off.
- Conversation Orchestrator manages the flow. It connects interactions across channels and manages handoffs between AI and human agents, effectively bringing individual touchpoints together into a single thread.
- Conversation Intelligence adds a real-time layer, analyzing live interactions for signals like sentiment and escalation risk, and triggering actions while the conversation is in progress.
The company hopes this will allow businesses to move from reactive engagement to something closer to continuous interaction.
This shift reflects a broader shift in how companies think about AI in customer experience. The question is no longer whether AI can respond to customers, but whether it has enough context to respond well. The framework of Twilio is that the real bottleneck is not the model. It is the infrastructure that connects everything around it.
More new features
The company also focuses on flexibility. With Agent Connect, developers can integrate different AI models or frameworks without rebuilding their communication 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 extends its channel and platform capabilities. This 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 a built-in assistant.
Early customer examples indicate practical use cases. Businesses use the platform to recover blocked apps, guide live conversations with real-time data, and reduce the need for repeated manual follow-ups. In each case, the common thread is continuity: moving the context forward rather than starting from scratch.
