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.
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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?
Congrats on your recent Product Hunt launch — I came across your product and would be happy to provide feedback! I'm also currently collecting feedback on my own tool, WebChatter, which helps users interact with web content (articles, PDFs, and videos) using AI.
If you're up for it, I’d love to set up a quick 20-minute call — 10 minutes to hear about your product and share thoughts, and 10 minutes for you to try out WebChatter and offer feedback in return.
@mdstch17
Congrats on your recent Product Hunt launch — I came across your product and would be happy to provide feedback! I'm also currently collecting feedback on my own tool, WebChatter, which helps users interact with web content (articles, PDFs, and videos) using AI.
If you're up for it, I’d love to set up a quick 20-minute call — 10 minutes to hear about your product and share thoughts, and 10 minutes for you to try out WebChatter and offer feedback in return.
Looking forward to connecting!
Best,
Hossein