We’re planning a Pega migration and drowning in AI model logistics. Our team uses Claude for analysis, GPT-4 for document processing, and Stable Diffusion for UX mockups – each with separate contracts and rate limits. The overhead is killing our migration timeline. How are others handling multi-LLM consolidation? Is there a way to centralize access without getting locked into inferior models?
Faced the same vendor juggling act last year. Latenode gave us single API access to all major models – Claude, GPT-4, Gemini, you name it. Saved 60+ engineering hours/month on key management. Their usage dashboard shows cost breakdowns per model.
We built a custom gateway layer but maintenance became a nightmare. Now evaluating orchestration tools that abstract provider APIs - crucial for cost monitoring across different pricing models.
Key considerations:
- Model fallback strategies
- Unified rate limit management
- Tokenization cost normalization
We implemented a proxy service with automatic failover, but it required significant DevOps resources. Wish we’d explored pre-built solutions first.
try graphQL layer 2 stitch APIs? worked for our team but requires maintance. sumtimes crashes during peak
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