Raghu Raghuram

Parasail has raised $32 million in a Series A round to expand its AI Supercloud platform, an inference and training layer for developer-controlled AI, bringing total funding to $42 million. The round was co-led by Touring Capital and Kindred Ventures, with participation from Samsung Next, Flume Ventures, Banyan Ventures, and existing investors. The San Francisco-based company, founded and led by CEO Mike Henry, is building a programmable global compute network that enables developers to deploy and scale AI models and agents with optimized performance, cost, and latency. Parasail said it will use the new capital to expand its platform, enhance inference and orchestration capabilities, and accelerate go-to-market efforts as demand grows for scalable, production-ready AI endpoints. FOUNDER: Mike Henry INVESTORS: Touring Capital, Kindred Ventures, Samsung NEXT, Flume Ventures & Banyan Ventures ROUND: Series A AMOUNT: $32,000,000 HQ: San Mateo, California #VentureCapital #Parasail #TradedPartner #MikeHenry #TradedVC

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World being super charged by AI, exponential growth of log/metrics must be processed and analyzed in an entirely new concept. Ingession based license model, Kafka based platform, is not a sustainable solution in the next era of exponentially growing log/metrics environment from cost and CPu resource perspective. FFWD brings a game changing solution holistically to the ever growing complex environment from network layer all the way up to AI Agent based on their in-house developed AI Native Pipeline framework, Anomally Detecion, and Correlation. When operating a large complex Enteprise environment, Data Center, AIDC, Service Infrastructure, SOC, etc., facing Mass Log/Metrics which is creating ever increasing license fees, servers, and etc. Check out how FFWD may solve your problem! https://www.core0.io/

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GPU supply forecasts tend to start at the fab. A second source is piling up at the decommission dock. Iron Mountain's asset lifecycle management business grew revenue 88% year over year in Q2. It's on pace to approach $1B this year, driven by AI and data center buildouts pushing hardware out of service. On today's Dynamo Show, Madelyn O'Farrell sat down with Tom Delahunty, VP of Operations for ALM at Iron Mountain, to unpack what happens to that hardware next. What stood out: - A hyperscale decommission starts with data sanitization and chain of custody. Nothing gets a second life until that's done - Remarketing cascades from full systems down to individual components - GPU-dense racks and liquid cooling raise the bar on testing, and ITAD capability has to catch up - Tom expects used GPUs to become a normal part of procurement, with the industry maturing toward something like the used car market - He makes the case for more R&D in reuse and critical mineral recovery For founders building in the reverse flow of compute, that R&D gap is the opening as we're here for it at Dynamo Ventures. Full episode in the comments 👇🏽

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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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I published a new piece with Silicon Foundry on a pattern that keeps repeating in AI infrastructure. Market leaders rarely miss these shifts because they’re asleep at the wheel. They miss them because they’re doing what leaders are trained to do. They run the playbook that made them leaders. They optimize the system they already have. And they trust the signals that have always correlated with strength. The problem is that AI infrastructure is not just more of the old stack. When architectures move, the basis of competition moves with them. Categories get redefined quietly, then all at once. By the time the change shows up cleanly in the numbers, the advantage has already migrated to a different layer of the value chain. In the article, I walk through why this happens and what to do about it. The ability to notice when the stack is reorganizing, before your planning process forces the answer back into last year’s categories. If you’re operating in semis, networking, or data center infrastructure, I’d be interested in how you’re watching for these shifts in your own system. https://lnkd.in/gimKJPUu

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Anthropic just committed $100M to launch the Claude Partner Network. The capital will fund training, certification, and joint GTM for consulting firms and system integrators. They are moving beyond direct API sales to activate a network of software vendors to deploy Claude at scale. Ecosystem building is the new moat in enterprise #AI. The AI war has shifted from training the smartest models to owning the distribution channels.

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