Prismatic Labs builds the environmental layer for AI: open-core infrastructure that makes runaway inference visible, measurable, and controllable.

As AI systems scale, their physical costs are becoming harder to ignore. Every wasted LLM call consumes compute, energy, carbon, latency, and budget - yet most teams still see only aggregate spend after the damage has happened. 

Production AI needs feedback loops that connect digital decisions to their real-world resource impact.

Our flagship tool, Vetch, helps teams detect and control inference waste in live LLM systems. It observes metadata only - never prompts or completions - to surface stalled agent loops, RAG bloat, prompt-caching opportunities, unattributed spend, and other patterns that quietly compound across production workloads. The roadmap extends this from observability into control: for high-confidence cases, Vetch will be able to warn, stop, or reroute waste before the next unnecessary call.

Prismatic Labs is building toward a broader open infrastructure stack for inference efficiency: attribution, benchmarks, energy and carbon methodology, production-safe controls, and optimisation agents that help AI systems become cheaper, faster, and less resource-intensive without compromising privacy or reliability.

We believe the next generation of AI should not just be more capable. It should be more aware of the physical systems it depends on - and able to act accordingly.

Prismatic Labs

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Prismatic Labs

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