How Do You Manage Multiple AI Model APIs in One Application?

As AI applications become more sophisticated, developers often need to work with multiple models for different tasks — coding, reasoning, content generation, and more.

But managing multiple providers can introduce some practical challenges:

• Different API keys and endpoint configurations

• Different request formats and model parameters

• Switching providers when a model is unavailable

• Tracking usage and understanding the actual cost

• Maintaining integrations as models and providers change

I'm interested in how other developers approach this.

A few questions for the community:

1. Do you integrate each AI provider directly, or use a unified API gateway?

2. How important is automatic failover when a model or provider becomes unavailable?

3. What matters most when choosing an AI API platform: model selection, reliability, pricing transparency, or ease of integration?

4. What limitations have you encountered when switching between different AI models?

We've recently launched HefuAI Platform, which provides access to 125+ AI models through a unified API, with OpenAI-compatible and Anthropic-compatible endpoints.

We're exploring ways to make multi-model integration simpler for developers, and I'd genuinely like to learn from the community's experience.

Website: https://hefu.hk

What's your current approach to managing multiple AI model providers?