“Model APIs fail, change, and latency spikes. Ember provides a unified, highly optimized gateway that handles caching, cost controls, and fallback routing automatically.”
The Problem
Directly integrating multiple LLM providers leads to messy API wrappers, high API costs from duplicate prompts, and unpredictable downtime when providers go offline.
The Solution
Ember is a lightweight proxy that unifies access to OpenAI, Anthropic, Gemini, and local models. It features semantic prompt caching, cost limits, auto-fallback, and real-time observability logs.
Story of the Craft
We built Ember to insulate Meros products from API failures. When one LLM provider had an outage, our products automatically switched to a backup model without the users noticing. We realized this routing layer is essential infrastructure for any AI engineering team.
Core Capabilities
Semantic Caching
Saves up to 60% on token costs by matching semantically similar prompts and returning cached responses.
Smart Fallbacks
Detects rate limits and server errors, instantly rerouting traffic to fallback models within milliseconds.
Token Rate Limits
Allows developers to configure custom spend caps per user, project, or API key in real-time.
Technical Architecture
High-performance Rust-inspired Go or TypeScript proxy deployed on Vercel Edge. Utilizes Redis Cluster for caching and real-time token bucket rate limiting.
Performance Statistics
Cost Savings
Reduction in monthly LLM spend via semantic caching.
Uptime
Maintained throughout multiple upstream cloud outages.
Proxy Latency
Ultra-fast routing overhead with zero blocking.
Ready to ship Ember to production?
Connect via our developer client console or integrate with our centralized API. Set up in less than five minutes.
