Introduction
What ConvoMem is, the problem it solves, and how the memory layer fits into your stack.
ConvoMem is a memory layer for conversational AI. It captures what happens in customer conversations, distills durable facts, and injects the relevant context back into every future interaction — so your bots and agents never start from zero.
Why customer memory matters
Most support stacks are stateless. Each new chat, call, or email begins without any knowledge of the customer's history: the issue they raised last week, the plan they're on, or the preference they stated twice already. The result is repetition, friction, and escalations that a little context would have avoided.
ConvoMem closes that gap with three primitives:
- Capture — ingest conversations from chat, voice, email, and SMS.
- Extract — turn raw transcripts into structured, scored facts.
- Retrieve — surface the right context at the start of the next conversation.
Who it's for
ConvoMem is built for teams running support bots, voice agents, or human-in-the-loop help desks who want continuity across sessions without building a memory pipeline themselves.
You bring the conversations; ConvoMem handles extraction, durability scoring, PII redaction, and retrieval. It's transport-agnostic and works alongside whatever LLM or agent framework you already use.
Where to go next
- New here? Jump into the Quick start — working code in under 10 minutes.
- Want the mental model first? Read How it works — pipeline, identity routing, and durability scoring explained.