# Executive Summary ## The world’s first AI Layer 0. Spin up chains, clusters, or custom models on enterprise-grade GPU infra. Backed by the co-founder of USDT and many more. Planck is working on building the AI computing stack of tomorrow. We try to accomplish the wide goal of delivering a sophisticated AI computing stack that includes the AI computing infrastructure, AI Studio, foundational models, industry vertical nodes, and AI powered-end applications. The AI computing stack we built can assist consumers, startups, enterprises, and scientists in the US and Asia, in developing their AI applications or AI models. We built two platforms that facilitate AI development and research across different sectors of industries. By combining a modular Layer-0 (Planck₀) with a compute-native Layer-1 (Planck₁), Planck delivers composable blockchain architecture and GPU-rich execution environments optimized for AI workloads, agent economies, and sovereign appchains. **Core Components:** * **Planck₀** — Modular Layer-0 for launching AI-native L1s, rollups, and DePINs with shared security and interoperability * **Planck₁** — A sovereign L1 compute chain with native GPU scheduling, inference, and payments * **GPU Console** — Decentralized bare-metal GPU cloud, live across global Tier-1 data centers * **AI Studio** — Platform for training, fine-tuning, and deploying foundation models **Key Stats & Highlights:** * $60M+ in deployed H100s, H200s, and B200s * Over $1M in platform revenue * 90% cheaper compute vs. hyperscalers like AWS * Backed by leading investors: Brock Pierce, Scott Walker, GDA Capital, DePIN X * Team from Google Cloud, Nvidia, Coinbase, Polkadot, and NEAR * Strategic partnerships: Microsoft, AWS, Nvidia, Chainlink Planck is not another cloud or chain—it’s the compute and coordination layer for decentralized AI at scale. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://resources.plancknetwork.com/planck/executive-summary.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.