We’re helping organizations embrace frugal observability—because inefficient code drives up compute costs and degrades user experience. As open-source LLMs enable more enterprises to distill their own models and run inference, COGS (Cost of Goods Sold) and sustainability have become paramount considerations in AI infrastructure investments.

zymtrace, an eBPF-powered continuous profiling platform, delivers deep system visibility into CPU⇄GPU interactions with actionable recommendations that guide engineers toward the highest-impact optimizations. It provides zero-instrumentation, cluster-wide observability across heterogeneous workloads, enabling users to maximize throughput per GPU, per dollar, per watt.

Our mission is to accelerate the world’s transition to cost-efficient and sustainable computing. By helping engineers understand the unit economics of their code across general-purpose and AI-accelerated workloads, zymtrace builds a culture where software efficiency is a shared value—and where creating software that’s faster, cheaper, and greener becomes second nature.

Join us on this exciting and challenging journey to build the next-generation distributed continuous profiler for modern heterogeneous computing environments.