Twilio has today announced the launch of its next-generation customer engagement platform designed for the agentic era.
With Twilio SIGNAL 2026 now underway, this platform enables AI agents to participate alongside humans in real-time conversations, offering four new capabilities to act as an infrastructure layer for persistent, context‑rich conversations across channels.
By positioning itself beyond CPaaS tooling and toward a foundational customer engagement platform, this approach aims to eliminate fragmented interactions for one continuous, remembered conversation.
Khozema Shipchandler, CEO at Twilio, argues that as AI agents become active participants in customer conversations, businesses need a shared infrastructure that treats humans and AI equally.
“The agentic era is here. Agents are joining conversations alongside the people they represent and modern customer engagement requires an infrastructure that serves both equally,” he said.
“Twilio’s new platform is the foundational infrastructure layer that makes every conversation persistent, contextual, and actionable – ensuring interactions feel like part of one continuous relationship.”
CPaaS Tooling in the Agentic Era
Twilio’s strategic move from being a communications API provider toward an always-on customer engagement infrastructure platform reflects the reality that in the agentic era, simply delivering messages and calls isn’t enough.
Today, businesses require shared memory, context, and orchestration to manage continuous conversations across humans, AI agents, and systems, as conversations are no longer simple, one-off exchanges.
Moving beyond traditional CPaaS tooling shifts Twilio from enabling communications to managing the entire customer relationship across every interaction.
With a CPaaS model, they can deliver a text or initiate a call, but they do not inherently understand who the customer is, what happened in previous interactions, or what should happen next.
As a result, businesses are responsible for stitching together customer context, conversation history, routing logic, analytics, and AI workflows, creating fragmented experiences that struggle to support continuous, agent‑driven conversations at scale.
This also limits how effectively businesses can deploy AI, because AI agents need access to context, memory, and workflow logic to deliver useful outcomes.
Messaging and voice infrastructure are increasingly competitive and can become commoditized over time, and with many providers able to deliver communications at scale, this puts pressure on pricing and reduces differentiation.
Staying solely in CPaaS could risk Twilio being seen by enterprise customers as an interchangeable infrastructure vendor rather than a strategic platform partner.
An Always‑On Layer for Customer Conversations
Twilio’s next generation platform acts as an always-on infrastructure layer that sits above individual channels, maintaining a single, persistent conversation state that carries context, memory, and intent across every touchpoint.
As conversations move between channels, AI agents, and human agents, the platform orchestrates routing, handoffs, intelligence, and actions in real time, ensuring every participant operates with a shared understanding of the customer and the relationship.
Inbal Shani, CPO and Head of R&D at Twilio, explains how this new platform allows businesses to carry context across interactions, so conversations feel continuous and informed.
“Most brands still treat every conversation with a customer like it’s the very first one,” she said.
“Twilio is changing that at the infrastructure layer, so every business built on Twilio can remember, learn, and respond like they actually know their customers.”
Twilio’s four new platform capabilities function as add-on infrastructure layers that extend Twilio beyond its traditional CPaaS products.
Conversation Memory
This platform capability offers persistent, cross‑channel memory for customer interactions by continuously extracting and maintaining relevant context such as conversation history, preferences, behavioral signals, and current state.
As a result, this makes that information available to both human agents and AI agents in real-time and ensures conversations pick up exactly where they left off.
For customers, this eliminates the need for them to repeat themselves and enables agents to respond with full awareness of past interactions.
Conversation Orchestrator
This turns fragmented calls and messages into a single, continuous conversation to ensure continuity is preserved as interactions move between voice, messaging, bots, and live agents.
It manages routing, escalation, state transitions, and seamless handoffs between AI, humans, and systems across multiple channels, maintaining a unified conversation layer.
Conversation Intelligence
This model-agnostic capability applies generative AI across live conversations to produce real‑time insights and actions.
By analyzing voice and messaging interactions as they happen, this capability surfaces guidance to human agents and triggers automated workflows based on intent, sentiment, and outcomes.
As a result, this enables businesses to enhance agent performance and operational efficiency while embedding intelligence directly into the flow of the conversation.
Agent Connect
As an open‑source, model‑agnostic framework, this capability connects AI agents directly to Twilio’s voice and messaging channels by allowing businesses to deploy, swap, or scale AI agents without rewriting channel integrations.
By removing the complexity of real-time interactions, this gives companies flexibility to choose their preferred AI models while relying on Twilio for the underlying communications and orchestration layer.
Where AI and Human Support Work Together
For CX teams, this platform creates more seamless and personalized experiences where customers can be recognized based on previous interactions, allowing businesses to respond faster and with greater relevance.
As a result, human agents are no longer required to gather background information as AI agents can engage with a deeper understanding of customer intent and history, reducing overall customer effort, shortening resolution times, and improving consistency across touchpoints.
The platform also transforms how enterprises manage service delivery, enabling them to orchestrate customer engagement from a single infrastructure layer and hand off escalations, handoffs, workflow triggers, and next-best actions to an AI agent.
For customers, this enables a natural and relationship-driven experience, whilst allowing businesses to drive personalized support and engagement.
