Why AI agents need real-time context
An AI agent is grounded by the context it reads. Hand it a stale snapshot and it responds to a situation that has already moved on. Real-time context keeps the agent aligned with what the user is doing right now.
The decision is built from context
An agent reasons over what it is handed. Give it last night’s snapshot and it answers for who the user was, not who they are this session. For anything that happens in the moment (support, shopping, onboarding), the context has to describe now.
What counts as current context
Real-time context is the running state of the current interaction: the last few actions and when they happened, the page or screen in view, a step that failed, how long the user has been stuck. It updates as the user acts and is available the instant the agent reads it.
Why real-time context pays off
An agent with real-time context can open with what is actually happening: that the user has been on the same page for four minutes, that their last payment failed, that they just compared two plans. That is the difference between an assistant that helps and one that asks what you need.
See it on your own traffic
Add the SDK, define one attribute, and see an attribute updating against your own traffic in the first session. The free tier runs on the real engine: no card, no sales call.