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Micheal Heypico
Micheal Heypico

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Model failover for AI apps: stop writing retry loops, start routing

Model failover for AI apps: stop writing retry loops, start routing.

Like a lot of teams, our AI stack was four subscriptions deep: ChatGPT Plus, Claude Pro, Gemini, and a transcription tool. US$80 a month, four logins, and comparing models on the same task meant copy-paste between tabs.

We consolidated into HeyPico — 32 frontier models behind one OpenAI-compatible key — and the architecture decisions that mattered most:

One endpoint, every provider

Every model behind our key speaks the OpenAI chat-completions format:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_HEYPICO_KEY",
    base_url="https://api.heypico.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-5.6",  # or claude, gemini, deepseek, glm, grok...
    messages=[{"role": "user", "content": "Summarize this transcript"}]
)
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Change one string, get a different provider. Your retry logic, logging, and eval harness stay untouched.

Failover is a config change, not a retry loop

We got throttled by a provider mid-demo once. With routing in place, failover becomes:

  • Coding tasks: primary Claude, fallback GPT
  • Long-context summarization: primary Gemini, fallback DeepSeek
  • Cheap bulk classification: GLM or Qwen

Your product stops dying when one provider has a bad day.

Prompt versioning from day one

Prompts are code. We keep ours in git and test every change against 3+ models before shipping. Structured output is where providers differ most — test that path specifically.

Try it

HeyPico is Singapore-based, CASA Tier 2 certified, and your data never trains models. First 100 developers get a free trial: heypico.ai/api-integration

We run a Telegram community where builders tell us what breaks: t.me/heypico

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