Use case
condense.chat helps chat products lower prompt and history cost.
Use condense.chat when system prompts, conversation history, tool schemas, and product context make each model call expensive. The product is positioned as a transparent layer that reduces oversized request context without changing the rest of the response flow.
What problem it solves
- Growing message history that inflates per-turn cost
- System instructions that stay important but are expensive to resend
- Tool schemas and product context that crowd out user-relevant working room
- Latency and spend pressure at high conversation volume
Why it fits product teams
The public site describes condense.chat as a drop-in proxy, which makes it easier for product teams to evaluate without rewriting business logic, tools, or model choice.
What stays the same
Your downstream model, your tools, and your client code can stay structurally familiar. condense.chat aims to make the request cheaper before it leaves your system.