Ratel is the context engine to make agents leaner, more accurate, and easier to debug.
Trusted by leaders at
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Accuracy on local models with small context windows
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Net tokens by loading only the context that matters
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Token cost on frontier models with stable accuracy
WHY RATEL
Token bills triple. Reliability drops. Ratel builds managed infra so you stay focus on the core, we let it run smoothly.
Supports any stack, any model
Seamlessly integrates in your stack, running on both cloud and local models
Reduces token bills
Only the right context at each turn is loaded, maxing token efficiency
Increases agent reliability
Every new data point improve agents instead of bloating context
USE CASES
Try now Ratel
At Ratel we also ship OSS products that helped us when building agents daily. We thought it might help you to!
pnpm add @ratel-ai/sdk
~70% higher accuracy on Qwen 3.5
62% more accuracy on Opus 4.7 with 83% less tokens
