enso/README.md

Enso

Enso is Hanzo AI's frontier model family and the router behind auto: every request is classified, priced against what your org can serve, and answered by the model that should answer it. Three tiers keep their order on quality and price as the models under them change.

Model	For
enso-ultra	the hardest problems, top-tier accuracy
enso-pro	everyday work at frontier quality
enso-flash	high volume, low latency, low cost
enso-auto	let the router pick for each request

Enso is a Hanzo AI original: proprietary and closed source. There is no code or weights here; it is served only through the Hanzo API.

• Model Card: Architecture, Benchmarks & Economics · Hugging Face Hub
• Benchmarks, measured on one harness: hanzo.ai/models/enso
• Docs: docs.hanzo.ai/docs/models/enso

Use Enso through the Hanzo API

curl https://api.hanzo.ai/v1/chat/completions \
  -H "Authorization: Bearer $HANZO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "enso-auto", "messages": [{"role": "user", "content": "Hello"}]}'

The API speaks the OpenAI wire format, so any OpenAI SDK works with base_url="https://api.hanzo.ai/v1".

Examples

Runnable client examples in this repository:

• Python: examples/python/client.py

  pip install -r examples/python/requirements.txt
  export HANZO_API_KEY="your-api-key"
  python examples/python/client.py
  

• TypeScript: examples/typescript/client.ts

  cd examples/typescript
  npm install
  export HANZO_API_KEY="your-api-key"
  npm start
  

• Go: examples/go/main.go

  export HANZO_API_KEY="your-api-key"
  go run examples/go/main.go
  

• Rust: examples/rust/

  export HANZO_API_KEY="your-api-key"
  cargo run --manifest-path examples/rust/Cargo.toml
  

• cURL: examples/curl/chat.sh

  export HANZO_API_KEY="your-api-key"
  ./examples/curl/chat.sh
  

Production Rust Recipes

recipes/: Modular, typed Rust patterns for model routing:

• ModelSuitabilityRecipe: Single-shot classification predicting optimal model capability tier given prompt tokens, domain, and latency/cost bounds.
• ConfidenceGate: Evaluates Kai decision margins (\Delta = P_{(1)} - P_{(2)}) against threshold \tau for low-latency fast decisions vs. LLM escalation.