Private Markets, Angel and Secondary Investing, Sacra

Sacra

Bringing transparency to private markets so investors, founders, and employees can build on conviction.

Sacra delivers deeply researched insights on the private companies shaping tomorrow's markets. By surfacing the data, context, and operator perspective that are missing from private markets today, we help secondary buyers and sellers price equity accurately and unlock liquidity for the people building these businesses.

Private Markets, Angel and Secondary Investing

Bringing transparency to private markets so investors, founders, and employees can build on conviction. Sacra delivers deeply researched insights on the private companies shaping tomorrow's markets. By surfacing the data, context, and operator perspective that are missing from private markets today, we help secondary buyers and sellers price equity accurately and unlock liquidity for the people building these businesses.

Private Capital Markets

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<li>In a data center, hundreds of thousands of GPUs need constant shared access to training data, checkpoints, embeddings, model outputs, and agent memory, pushing AI labs (xAI), neoclouds (CoreWeave, Lambda, Crusoe), and hyperscalers (Microsoft, Google) toward VAST Data’s separated compute/shared flash architecture—which maps well to GPU clusters with many machines reading and writing to one data pool—versus high-speed storage systems designed for supercomputing (Weka, DDN) and reliable storage for basic IT (Pure, Dell, NetApp).</li>
<li>As AI shifts from chatbots to agents, massive amounts of unsupervised tool calls, generated code, and persistent agent memory require multimodal filesystems that handle PDFs, audios, and video rather than just structured data, and these compounding amounts of data must be stored and accessible via fast access, driving storage demand up and flash memory prices up 8x, a tailwind behind infrastructure that makes storage more efficient and works with low-cost or retrofitted flash.</li>
<li>The upside opportunity is to serve as the unifying AI software operating system that powers the infrastructure layer of NVIDIA CEO Jensen Huang’s AI five-layer cake, abstracting away the GPUs &amp; hardware underneath for the developers building models &amp; applications above, expanding the market from model companies &amp; neoclouds into the long tail of enterprises building their own secure, access-controlled agentic applications.</li>
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In a data center, hundreds of thousands of GPUs need constant shared access to training data, checkpoints, embeddings, model outputs, and agent memory, pushing AI labs (xAI), neoclouds (CoreWeave, Lambda, Crusoe), and hyperscalers (Microsoft, Google) toward VAST Data’s separated compute/shared flash architecture—which maps well to GPU clusters with many machines reading and writing to one data pool—versus high-speed storage systems designed for supercomputing (Weka, DDN) and reliable storage for basic IT (Pure, Dell, NetApp).
As AI shifts from chatbots to agents, massive amounts of unsupervised tool calls, generated code, and persistent agent memory require multimodal filesystems that handle PDFs, audios, and video rather than just structured data, and these compounding amounts of data must be stored and accessible via fast access, driving storage demand up and flash memory prices up 8x, a tailwind behind infrastructure that makes storage more efficient and works with low-cost or retrofitted flash.
The upside opportunity is to serve as the unifying AI software operating system that powers the infrastructure layer of NVIDIA CEO Jensen Huang’s AI five-layer cake, abstracting away the GPUs &amp; hardware underneath for the developers building models &amp; applications above, expanding the market from model companies &amp; neoclouds into the long tail of enterprises building their own secure, access-controlled agentic applications.


Renen Hallak, CEO Of VAST Data, On AI Agents Creating Infinite Storage Demand