Redis LangCache
Redis LangCache provides semantic caching-as-a-service to reduce LLM costs and improve response times for AI applications.
Redis LangCache is a fully-managed semantic caching service that reduces large language model (LLM) costs and improves response times for AI applications.
How LangCache works
LangCache uses semantic caching to store and reuse previous LLM responses for similar queries. Instead of calling the LLM for every request, LangCache:
- Checks for similar cached responses when a new query arrives
- Returns cached results instantly if a semantically similar response exists
- Stores new responses for future reuse when no cache match is found
Key benefits
Cost reduction
LangCache significantly reduces LLM costs by eliminating redundant API calls. Since up to 90% of LLM requests are repetitive, caching frequently-requested responses provides substantial cost savings.
Improved performance
Cached responses are retrieved from memory, providing response times up to 15 times faster than LLM API calls. This improvement is particularly beneficial for retrieval-augmented generation (RAG) applications.
Simple deployment
LangCache is available as a managed service through a REST API. The service includes:
- Automated embedding generation
- Configurable cache controls
- Simple billing structure
- No database management required
Advanced cache management
The service provides comprehensive cache management features:
- Data access and privacy controls
- Configurable eviction protocols
- Usage monitoring and analytics
- Cache hit rate tracking
Use cases
AI assistants and chatbots
Optimize conversational AI applications by caching common responses and reducing latency for frequently asked questions.
RAG applications
Improve retrieval-augmented generation performance by caching responses to similar queries, reducing both cost and response time.
AI agents
Enhance multi-step reasoning chains and agent workflows by caching intermediate results and common reasoning patterns.
AI gateways
Integrate LangCache into centralized AI gateway services to manage and control LLM costs across multiple applications.
Getting started
LangCache is currently available through a private preview program. The service is accessible via REST API and supports any programming language.
Prerequisites
To use LangCache, you need:
- An AI application that makes LLM API calls
- A use case involving repetitive or similar queries
- Willingness to provide feedback during the preview phase
Access
LangCache is offered as a fully-managed cloud service. During the private preview:
- Participation is free
- Usage limits may apply
- Dedicated support is provided
- Regular feedback sessions are conducted
Data security and privacy
LangCache stores your data on your Redis servers. Redis does not access your data or use it to train AI models. The service maintains enterprise-grade security and privacy standards.
Support
Private preview participants receive:
- Dedicated onboarding resources
- Documentation and tutorials
- Email and chat support
- Regular check-ins with the product team
- Exclusive roadmap updates
For more information about joining the private preview, visit the Redis LangCache website.