Mark Fernandes

Today, we're welcoming ORION Security to the Norwest portfolio. The #DLP market has grown to $5B, yet most solutions are still built on thousands of static, human-authored policies. Spending time with Nitay Milner (CEO & Co-Founder) and Jonathan Kreiner (CTO & Co-Founder) in Tel Aviv reinforced why ORION stands apart. Their work is grounded in firsthand experience with the limitations of legacy DLP, guiding their passion and urgency to pave the way for an autonomous, context-driven approach that confronts today’s evolving risks head‑on. Looking forward to seeing what the team builds next as enterprises adopt autonomous DLP at scale. 🔗 https://lnkd.in/gH7vXs4x  

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As AI workloads eat up global computing supply, DRAM prices are surging like never before—creating major challenges for teams trying to plan out their data center spend. One of my portfolio companies, Mext, is addressing the largest cost component in the datacenter: server memory (DRAM). From being on the board of Redis for the last twelve years, I’ve learned a lot about the various aspects of this problem and approaches to solving them. Mext found a breakthrough, using new AI techniques, for dramatically reducing the amount of server-DRAM required to run applications, all while maintaining performance. It intelligently manages the server’s memory, keeping hot pages (i.e., those in use by applications) in fast DRAM and offloading cold pages (i.e., those less used) to a much less expensive memory tier (e.g., NVMe Flash). Key to the approach is ensuring cold memory pages that are about to be accessed by an application are back in DRAM before the application needs them or notices that they were gone. This is done without modifications to the application or the OS – so it can run in the cloud or on-premise. Mext thus allows applications to either run using less DRAM or keep their DRAM footprint but do more with it. They're hosting a webinar along with Fred Weber (former CTO of AMD) on Jan 22nd at 10am pacific time. You can register here: https://lnkd.in/gXe9GCeE

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GPUs have gotten faster, and models have gotten larger. But storage is still stuck in the past. Modern AI workloads need instant access to huge datasets. Instead, teams waste time on slow retrieval, idle GPUs, and costly pipelines. Archil is changing this. It delivers object-storage scalability at block-storage speeds. The platform allows for seamless, high-performance access to massive datasets. By eliminating cold starts and accelerating throughput 30X, Archil enables teams to fully utilize their infrastructure and move faster on training, analytics, and AI deployment. Archil’s founder Hunter Leath brings rare technical depth and operating experience from building Amazon EFS and optimizing Netflix’s cloud performance. This is a team building the foundational layer that AI workloads desperately need. I’m thrilled to lead Archil’s seed at Felicis with Nancy Wang and support their mission to reinvent cloud storage for the AI era. https://lnkd.in/gWueXhzz

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As I'm leaving AWS re:Invent in Vegas, I’m reminded of a counterintuitive truth: competing with the public clouds is often really good business VCs love to ask, “Why wouldn’t the incumbent do this?” But in markets this large (and evolving this quickly) that’s rarely the right question. The real questions are: Who can assemble the best team, get to market fastest and with the most focus? And where are there opportunities to partner with the biggest players rather than compete? We’ve seen this pattern repeat across the ecosystem: -People assumed Vercel and AWS were destined to compete. Today, they’re strategic partners with CEO Guillermo Rauch in the keynote -Snowflake vs. Amazon Redshift. Now, AWS is one of Snowflake’s strongest distribution channels -In Datadog’s early pitches, the concern was, “If it’s just monitoring AWS, why not use CloudWatch?” Fast forward to now, and Datadog is now $50B+ public company We’re going to see the same dynamics play out with OpenAI and Anthropic. These are becoming foundational platforms. But that doesn’t preclude incredible companies from being built on, next to, and even around them. Some will look competitive. Many will end up as partners. And the biggest outcomes often start in those gray zones

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We at Sound Ventures are incredibly excited to share today we led WitnessAI's $58M raise, with participation from Fin Capital, Qualcomm Ventures, Samsung Ventures, and Forgepoint, alongside existing investors Google Ventures and Ballistic Ventures… And it is just the beginning 🙌 The primary barrier to enterprise AI adoption isn’t tech debt; it’s tech doubt. WitnessAI has proven it can instill confidence in AI adoption, and has done so for multiple global leaders. We are thrilled to support the team as they use this capital to expand into new markets and solidify their position as the leading standard for safe, secure enterprise AI. In our diligence, we spoke with dozens of Fortune 500 security leaders and heard a clear theme: teams want to move fast with AI, but need protections that scale. WitnessAI provides that through a full, end-to-end security platform spanning AI applications, models, and agents, seamlessly integrating into a company’s existing infrastructure. As AI moves from experimentation to execution, WitnessAI enables organizations to deploy AI broadly and responsibly. Led by Rick Caccia, a world-class operator with over two decades of experience building and scaling security businesses, WitnessAI is on a path to define the category for enterprise AI security.

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The old SaaS pricing playbook doesn’t work for AI. Madhavan Ramanujam and I partnered with Emergence Capital and Jake Saper to write a new one—built for where AI is going, not just where it is today. We lay out what state-of-the-art AI pricing looks like now—and what it will look like: ✅ Hybrid pricing (seats + usage) is the current best practice 🎯 Outcome-based models are the future—pricing tied directly to impact 💰 The best AI companies already capture 25–50% of the value they create As autonomy and attribution improve, outcome pricing will go from rare to expected. Founders who move early will win. Full read here 👉 https://lnkd.in/gwp6tDtp

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#AmTech Weekly Roundup: -> Clarium raised $27 million in Series A funding from Northzone, General Catalyst, AlleyCorp, and Kaiser Permanente Ventures. Clarium’s hospital supply chain management software works with crowdsourced data from providers, suppliers, and vendors to lower costs and prevent disruptions.   Steve Liou   -> Reflect Orbital raised $20 million in Series A funding from Lux Capital, Sequoia Capital, and Starship Ventures. Reflect Orbital builds satellites that reflect sunlight down to Earth for large-scale solar generation and night-time lighting for things like overnight construction projects, disaster relief, and public events.   Ben Nowack, Tristan Semmelhack    -> Adyton PBC raised $11 million in funding from Venrock, Khosla Ventures, Liquid 2 Ventures, Alumni Ventures, and Initialized Capital. Adyton’s defense-focused operational software gives warfighters access to information about resources, supplies, and support platforms.   JJ Wilson, James Boyd #VentureCapital #VC #USA #Startups

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On-Prem is the New Cloud: Why Enterprises are Reversing Stance in the Age of AI Remember when cloud was the battleground for innovation, agility, and scale? Everyone was tracking the % of on-prem compute moving to the cloud and it was growing every year? Well now there’s a reversal. The reality today? On-prem is the new cloud. Here’s why. AI’s Dark Side: Legal Risk and Data Governance Headaches Enterprises are excited about AI, but also uneasy as vendors like OpenAI face intensifying legal pressure. In a high-stakes lawsuit, a judge ordered OpenAI to preserve all ChatGPT chats (even deleted ones), overriding its 30-day deletion policy. Imagine that: you delete sensitive conversations, but they’re still sucked into legal limbo. The precedent is clear: AI prompts and outputs are discoverable records, demanding integration into enterprise ESI (Electronic Stored Information) policies. For large organizations handling sensitive data, the risk is simple: you can’t afford your AI tools to turn into legal liabilities. Especially when global regulations (GDPR, etc.) and internal governance collide with unpredictably broad discovery orders. Sovereignty, Control, Trust Many enterprises still ban ChatGPT or impose strict rules on usage. Even when allowed, token limits are throttled. Enterprises are cautiously letting AI in (as they should). Enterprises need to have control and trust. SAP is leaning into this with its Sovereign Cloud On-Site, deployable on customer premises with SAP-managed infrastructure. It is built to deliver data, operational, technical, and legal sovereignty in one package. Doubt it will be the last. Scaling Pains Talking to founders, three reasons stand out why cloud isn’t scaling with AI: 1/ The rate at which AWS/GCP lets you provision compute and the compute it wants you to provision both falter as AI and AI driven developers deploy a lot more code more frequently than before. So sometimes it’s not about data governance, but actually about performance and functionality. 2/ Shadow AI is rampant—employees paste sensitive info into models despite restrictions—creating demand for better permissioning tools. 3/ Data leakage remains a live risk, like the August 2025 Grok incident where hundreds of thousands of private chats became publicly accessible and indexed. One thing is for sure - founders selling into the enterprise are scaling faster if they offer the ability to run on-prem. The Future is Hybrid Don’t get me wrong - cloud is not going anywhere. But neither is on prem. A few years agoI thought we were headed for a full cloud shift, but now I think the future is truly hybrid.

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Camber Creek led the $3.7 million Seed round for TwinKnowledge, which is tackling an important problem in the built environment. Construction projects get delayed and rework is required because of discrepancies across construction documents, submittals, requests for information, design, and other plans. TwinKnowledge’s AI Agents absorb structured and unstructured project data, surfacing and preventing conflicts before the work begins. We’re excited about our partnership with CEO Ivan Panushev and his team. #construction #AEC #AI #technology https://ow.ly/mBYX50VtaVG

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