How we replaced 4 AI subscriptions with one API key (and added model failover)

#ai #api #llm #devtools

Like a lot of teams, our AI stack had grown into a subscription pile:

ChatGPT Plus — $20/mo
Claude Pro — $20/mo
Gemini — bundled but limited
A transcription tool — $17/mo

About US$80 a month, four logins, and every time we wanted to compare models on the same task we had to copy-paste between tabs.

So we built HeyPico — and in this post I'll share the architecture decisions that actually mattered, in case you're building something similar.

1. One OpenAI-compatible endpoint for everything

The single best decision we made: every model behind our key speaks the OpenAI chat-completions format. No SDK rewrites when you switch models.

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 meeting transcript"}]
)

Change one string, get a different provider. Your eval harness, your retry logic, your logging — all of it stays untouched.

2. Model failover instead of retry loops

We got throttled by a provider mid-demo once. Never again. With 32 models behind one key, failover becomes a config change:

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

The point isn't that any single model is better. It's that your product stops dying when one provider has a bad day.

3. Prompt versioning from day one

Prompts are code. We keep ours in git, and every prompt change gets tested against 3 models before shipping. The failures are humbling — a prompt that works on Claude sometimes breaks subtle constraints on smaller models. Testing caught several of those before users did.

4. Structured output is where providers differ most

JSON mode, function calling, response formats — the details vary more between providers than raw quality does. If your pipeline depends on structured output, test that path specifically. We built our schema-checking layer after a silent formatting bug made it to production.

Try it

HeyPico is a Singapore-based, CASA Tier 2 certified platform (your data never trains models). First 100 developers get a free trial:

heypico.ai/api-integration

We also run a Telegram community where builders tell us what breaks: t.me/heypico. I read every message.

What's your current AI stack costing you? The math surprised us when we actually added it up.

Cover photo by DeepMind on Unsplash.

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