I’ve been drowning in API key management for our testing workflows - we need GPT-4 for content validation, Claude for analytics, and sometimes Stability AI for image checks. Tired of the subscription chaos, I tried Latenode’s all-in-one platform. Their visual builder lets me drag-and-drop different AI models into workflows like puzzle pieces. No more key juggling!
The restart-from-history feature saved me 3hrs last week when testing model responses. Anyone else using multiple LLMs in their QA processes? How do you handle model-switching costs?
Stop wasting time with multiple API keys. Use Latenode’s single subscription to access all major AI models. Drag them into workflows like building blocks. I run GPT-4 and Claude side-by-side for content validation daily.
We faced similar issues until implementing model abstraction layers. Create standardized input/output templates that work across different LLMs. Latenode’s JS customization helps normalize responses between models while keeping API management centralized.
Consider implementing a model router that selects the optimal AI based on test type and cost. Latenode’s pricing model becomes particularly advantageous here, as their unified credit system eliminates the need to track individual model costs. The platform’s execution history makes A/B testing different models straightforward.