dot Redis LangCache and the next era of fast, accurate AI are here.

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LangCache uses semantic caching to store and reuse previous LLM responses for repeated queries.

Instead of calling the LLM again for every request, LangCache checks if a similar response has already been cached and returns it instantly, saving time and money.

How it works

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Use cases

Optimizing AI assistants with RAG plus-white minus-white

Use LangCache to optimize chatbots and agents with decreased costs and faster responses.

See RAG architectures

Build efficient agents plus-white minus-white

Agents and multi-step chains of reasoning take longer and cost more due to multiple LLM calls. Improve performance with our semantic caching-as-a-service.

Learn agent infrastructures

Improve your AI gateway plus-white minus-white

For companies building centralized services to manage and control LLM costs and security, LangCache is a key component for fast and efficient AI gateways.

Enhance your AI gateway

Get started

Register to join our private preview.

Frequently asked questions

Who's eligible to participate in the private preview? plus-white minus-white

The private preview is open to devs, product teams, and orgs working on GenAI apps including RAG pipelines or agents. Participants should have relevant use cases and be willing to provide feedback to help shape the product.

Is there a cost to participate in the private preview? plus-white minus-white

No, participation in the private preview is free. However, there may be usage limits or specific terms of use during the preview phase. When the private preview ends, accounts will be migrated to paying accounts.

How is the product deployed or accessed (e.g., APIs, SDKs, cloud services)? plus-white minus-white

LangCache is a fully-managed service available through a REST API interface and can be used with any language. No database management is needed.

How does the product handle data security and privacy? plus-white minus-white

Your data is stored on your Redis servers. Redis doesn’t have access to your data nor do we use your data to train AI models.

What kind of support is available during the private preview? plus-white minus-white

You’ll receive dedicated onboarding resources with docs, email, and chat support for troubleshooting, as well as regular check-ins with the product team for feedback and issue resolution.

How can I learn more about the product’s roadmap? plus-white minus-white

Participants will receive exclusive updates on the product roadmap during the private preview. Additionally, roadmap insights may be shared during feedback sessions or other communications throughout the preview.