Voice agent with awareness
Context at conversation speed
A voice agent that knows the account history and retrieves it fast enough that the caller never hears it thinking.
The problem
Voice is unforgiving about latency
In chat, a two-second pause is invisible. On a call, it's the moment the caller says "hello?" and decides they're talking to a machine.
That leaves voice agents with a bad choice: skip retrieval and stay fast but contextless, or retrieve and introduce a pause that breaks the conversation. Most pick fast, which is why voice agents ask questions the company already knows the answer to.
What makes it work
Retrieval inside the natural pause
On a call there is no loading state. Either the context arrives before the caller notices the gap, or the agent answers without it.
Low-latency retrieval
Zenmem returns context in — well inside the gap between a caller finishing a sentence and expecting a reply.
Account memory in real time
Previous calls, tickets, and what was tried, retrieved mid-conversation without a pause the caller notices.
Session continuity
Long calls hold context throughout. What the caller said at minute two is available at minute fifteen.
Self-hosted, so it's co-located
Running on your own infrastructure removes the network hop to a vendor API, which is a meaningful share of the latency budget in a voice pipeline.
Where the budget goes
The latency math
A natural conversational turn allows roughly 300–500 ms before a pause becomes noticeable. Speech-to-text, model inference, and text-to-speech consume most of it.
Retrieval has to fit in what's left, which is why memory that adds 200 ms is unusable in voice regardless of how good the context is. Self-hosted, co-located retrieval is the only version of this that works.
FAQ