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The idea of routing LLM prompts dynamically between cloud and edge is super compelling — especially with agents monitoring things like compute and connectivity. Curious from a technical perspective: how are you handling model compatibility between local and cloud environments? Do you support fallback across models with different tokenizers or context limits?
Oblix.aiOrchestration between cloud/local LLM
Oblix is a smart orchestration layer for LLMs that dynamically routes prompts between cloud APIs and edge models based on real-time signals like compute availability, network conditions, privacy, and cost—enabling reliable experiences across environments.
Oblix.aiOrchestration between cloud/local LLM