ML Infrastructure
Make deep agentic workflows viable on limited hardware
CLC Runtime is a node-local latent execution runtime for multi-step workflows with shared context. Optimized for avoided recompute on single-node or small-cluster deployments where hardware resources are constrained.
- →Deeper workflows without exponential cost
- →Lower latency on shared-context pipelines
- →Predictable spend for verifier and retry loops
Designed for teams already running multi-step AI workflows in production.
What CLC Does
CLC Runtime reduces redundant computation in deep, multi-step agentic workflows. It operates at the execution layer, identifying and eliminating repeated prefill processing across sequential workflow steps.
CLC delivers its strongest economic and latency gains when repeated prefill dominates execution cost; in highly optimized, high-concurrency clusters, its value shifts to predictable session behavior rather than additional speed.
CLC runs node-local alongside standard inference runtimes. It does not replace engine-level optimizations and does not move computation across nodes.
Who It's For
CLC is designed for Phase-1 buyers: teams transitioning from API-only inference to self-hosted deployments.
- —You're transitioning off API-only inference to self-hosted deployments
- —You run single-node or small-cluster deployments (not fully distributed)
- —You operate long-context, multi-step workflows with shared context
- —Cost predictability matters more than peak throughput
- —Hardware resources (VRAM) are constrained
- —You only use hosted API providers (OpenAI, Anthropic)
- —You operate fully optimized, high-concurrency inference clusters where prefix reuse is already amortized
- —You need cross-node computation portability or distributed optimization
- —You're focused on single-turn interactions without workflow depth
Why CLC Runtime
Avoided Recompute
Eliminates redundant prefill processing across sequential workflow steps, reducing cost and latency when repeated context dominates execution.
Node-Local Execution
Runs alongside standard inference runtimes without replacing engine-level optimizations. Computation stays on-node.
Predictable Behavior
Enables consistent reuse behavior across workflow steps, providing predictable outcomes for production workflows.
See if your workflows are recompute-bound
Evaluate CLC locally. Local installation, no data sent back. Designed for side-by-side baseline comparison.