Continuum

What it does

AI workflows today are built from disconnected calls that do not share work. The same prompts and tokens are recomputed across steps, which wastes time and cost. Continuum treats workflows as executable graphs where tokens, tensors, and tools live in one system. It can reuse shared computation, such as long prompt prefixes, and optimize execution across runs. The result is faster agents, lower costs, and a system that understands what it is doing.

Unified execution runtime for LLM and ML programs. - GitHub - rithulkamesh/continuum: Unified execution runtime for LLM and ML programs.

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