The Problem with Monogamy (in AI)

When we started building voice agents, everyone was obsessed with GPT-4. And for good reason—it's incredibly smart. But for voice? It's often too slow, or too expensive, or just... "too much" for simple tasks.

This is why Butter AI was built on a multi-provider architecture from day one.

Speed vs. Smarts

If you're building a receptionist agent, do you really need the reasoning capabilities of a PhD student to ask "What time would you like to come in?"

Probably not.

"The best AI model is the one that solves the specific task the fastest and cheapest, not the one with the highest benchmark score."

Enter The Mix

Here is how we recommend structuring your stack:

1. Router Layer: A cheap, fast model (like Haiku or GPT-3.5) determines the user's intent.
2. Specialist Layer:
   • Complex reasoning? -> GPT-4o
   • Creative writing? -> Claude 3.5 Sonnet
   • Quick lookup? -> Gemini Flash

How We Handle This

At Butter, we abstract this complexity. Through our dashboard, you can configure "Intelligent Routing" rules that swap models based on latency, cost, or specific conversation steps.

{
  "agent_config": {
    "default_llm": "gpt-4o-mini",
    "fallback_llm": "claude-3-5-sonnet",
    "stt": "deepgram-nova-2",
    "tts": "elevenlabs-turbo-v2"
  }
}

Stay tuned for more deep dives into our routing infrastructure and how you can use our Bento Grid of features to build your perfect agent.