Navin Chaddha
![Navin Chaddha is an influencer]()
Managing Partner at Mayfield | Inception and Early-Stage Investor | 3x Founder
Menlo Park, California, United States
62K followers
500+ connections
About
I know what it feels like to start with nothing but a thesis and a whiteboard.
I grew up in India, graduated from IIT Delhi, began a PhD at Stanford, and walked away because I couldn’t wait to build. I spent my 20s founding three companies: VXtreme (acquired by Microsoft to become Windows Media), iBeam Broadcasting (NASDAQ: IBEM), and Rivio (merged with CPA.com). Being a 3x founder taught me that company building is a marathon, markets are unpredictable, and the only constant is the quality of the people you surround yourself with.
When I crossed the table, I brought every one of those lessons with me. Twenty years later, I still operate in founder mode every day. I back founders primarily at inception, before the market believes. Under my leadership, Mayfield is investing $3 billion in AI, focused on the builders creating the future of AI.
Most investors define ROI as return on investment. I define it differently: Rise of the Individual. My role is to help people reach levels they never imagined possible.
Across my career, I’ve partnered with founders at 60+ companies creating more than $120B in equity value:
- 18 IPOs, including Akamai, Lyft, HashiCorp, Poshmark, SolarCity, MakeMyTrip, Persistent Systems, Matrimony.com, and Tejas Networks.
- 29 acquisitions, including Securiti.ai (Veeam), Nuvia (Qualcomm), Volterra (F5), Portworx (Pure Storage), CloudGenix (Palo Alto Networks), CloudSimple (Google), Gigya (SAP), StorSimple (Microsoft), and more.
I’ve been named to the Forbes Midas List 17 times - including Top 5 rankings in 2020, 2022, 2023, and 2024 - and recognized as a Young Global Leader by the World Economic Forum.
AI is the greatest opportunity of our lifetime - for founders, for businesses, for humanity. I love working with people who never stop learning, never stop growing, never stop giving their best. If you’re building the future of AI and put people first - let’s talk.
Articles by Navin
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Q1 2026 VC Outlook: The AI Power Law Era
Q1 2026 VC Outlook: The AI Power Law Era
We are in the “Winner Takes Most” Golden Era. In my two prior newsletters — Why 2025 is the Start of a Golden Era for…
6 Comments -
Founder Insights: Weekend Edition – Issue #27
Founder Insights: Weekend Edition – Issue #27
Spotlight: The AI Gold Rush: Money Today Is In Infrastructure In every gold rush, the miners get the headlines. But the…
14 Comments -
The AI Gold Rush: The Real Money Today is in AI Infrastructure
The AI Gold Rush: The Real Money Today is in AI Infrastructure
In every gold rush, the miners get the headlines. But the enduring fortunes are built by the people selling the picks…
33 Comments -
Founder Insights: Weekend Edition – Issue #26
Founder Insights: Weekend Edition – Issue #26
Spotlight: How College Students Should Think About Careers in the AI Era This week’s Spotlight is: How College Students…
16 Comments -
Founder Insights: Weekend Edition – Issue #25
Founder Insights: Weekend Edition – Issue #25
Spotlight: The Future of Sales and Role of the CRO This week’s Spotlight is: The Future of Sales and Role of the CRO…
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The Orchestrator CRO
The Orchestrator CRO
This is part 2 of a series on the Future of CXOs in the AI Era. Read the Architect CMO here.
25 Comments -
Founder Insights: Weekend Edition – Issue #24
Founder Insights: Weekend Edition – Issue #24
Spotlight: 3 Things CIOs Know That Every AI Founder Should Understand This week’s Spotlight is: 3 Things CIOs Know That…
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Q1 in Review: People First. From Inception
Q1 in Review: People First. From Inception
We entered 2026 saying this would be the year AI proves its economics - and Q1 delivered. It's been a milestone quarter…
14 Comments -
Founder Insights: Weekend Edition – Issue #23
Founder Insights: Weekend Edition – Issue #23
Spotlight: The OpenClaw Ecosystem This week’s Spotlight is: The OpenClaw Ecosystem. Linux didn't create the Internet…
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The OpenClaw Ecosystem
The OpenClaw Ecosystem
Linux didn't create the Internet, but it created the foundation on which everything else ran. OpenClaw is doing the…
69 Comments
Activity
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A major milestone for OpenLight: We’ve secured $50M in Series A-1 funding, bringing our total funding to $84M. This reflects growing confidence in…
A major milestone for OpenLight: We’ve secured $50M in Series A-1 funding, bringing our total funding to $84M. This reflects growing confidence in…
Liked by Navin Chaddha
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Introducing Outreach Omni – the universal conversational agent for revenue teams. We spent the last year building agents that…
Introducing Outreach Omni – the universal conversational agent for revenue teams. We spent the last year building agents that…
Liked by Navin Chaddha
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For decades, SaaS was about hiring software, buying licenses and giving people tools to do the work. Agentic AI changes that. Now you can hire…
For decades, SaaS was about hiring software, buying licenses and giving people tools to do the work. Agentic AI changes that. Now you can hire…
Liked by Navin Chaddha
Experience
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Board Member
Fungible, Inc.
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Board of Directors, Series Seed Lead
CloudSimple
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Board of Directors, Series Seed Lead
Brighter
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Entrepreneur in Residence
Mobius Venture Capital
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CEO & Founder
Rivio
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CTO and Founder
VXtreme
Education
Skills
Languages
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English
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Hindi
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More activity by Navin
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This week's spotlight is: The AI Gold Rush: Money Today Is in Infrastructure We're living through the AI gold rush, and real fortunes are being…
This week's spotlight is: The AI Gold Rush: Money Today Is in Infrastructure We're living through the AI gold rush, and real fortunes are being…
Shared by Navin Chaddha
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Conference prep used to mean Googling every attendee one by one. I arrived at a conference this week and got a list of 28 CEOs and their companies…
Conference prep used to mean Googling every attendee one by one. I arrived at a conference this week and got a list of 28 CEOs and their companies…
Liked by Navin Chaddha
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The best conversations happen when there’s no agenda. Last night, we brought together Mayfield CEOs, founders, leaders, and ecosystem partners for…
The best conversations happen when there’s no agenda. Last night, we brought together Mayfield CEOs, founders, leaders, and ecosystem partners for…
Shared by Navin Chaddha
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If I were running a legacy SaaS company today, I wouldn’t be sleeping much. For legacy SaaS startups, pivoting to an AI-native company is an…
If I were running a legacy SaaS company today, I wouldn’t be sleeping much. For legacy SaaS startups, pivoting to an AI-native company is an…
Liked by Navin Chaddha
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Brittany Walker
Voice is a super interesting modality right now - maybe the first modality we're seeing move to open source models across a number of scale ups / enterprises. Reliability concerns, high costs, and open source model performance are pushing engineers to do their own fine tuning vs. relying on third-party vendors of proprietary models. Many of these orgs have already been collecting their own first-party data and now with third-party vendors like Extrian, David AI, etc they can train really high quality models. RL has been insanely hyped, but it's been unclear how long it will take scale ups and enterprises to actually lean in. Voice AI might be hitting that inflection point faster than expected.
7 Comments -
Maria Palma
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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Carlotta "Lotti" Siniscalco
The best AI apps today are being built like infrastructure companies. Great breakdown from the awesome 💡 Yazan "Yaz" El-Baba on why technical depth, rapid iteration, and margin-aware architectures are becoming table stakes for AI startups. Definitely worth a read: https://lnkd.in/gMVFFXgH
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Nick Durham
I’ve been working on the theory of why small, shippable factories are the perfect inversion to the centralized prefab factory model. It all collapsed into one line of math (credit to Gilles Retsin): Factory Efficiency = Usage × (Throughput × Product Value ) / ( CapEx + Deployment OpEx) The idea is that the closer you can drive Usage to 100 % while keeping the denominator tiny, the faster the flywheel spins. A shippable microfactory tackles this by primarily focusing on a high Usage factor. Because the microfactory can be packed up afterwards and reused, its CapEx gets amortized over multiple projects, effectively raising its overall Usage across the year. If one project alone doesn’t fully occupy the factory, it can simply roll over to another job to maintain high Usage. Its CapEx is often an order of magnitude lower than a centralized factory (< $1M vs. $10-50M min), so the breakeven throughput is more achievable on a small pipeline of work. The real breakthrough here is portability. There is near-zero stranded capital and almost no idle time. To flesh this theory out, I wrote 3000 words on the topic for Brad Hargreaves and Thesis Driven. The article breaks down: - why “fixed factories, shipped goods” is being inverted to shipped factories, fixed goods - what a sub‑$1 M robotic cell does to CapEx per home versus a £45 M off‑site plant - early production/cost data on a shippable microfactory from Mollie Claypool, Gilles Retsin, Sam Baker and the Automated Architecture (AUAR) team - the hybrid reality of robots tackling the heavy structural components and human crews assembling faster and cheaper - technical constraints to pull this model off and future considerations on the optimal business model (own vs. rent) Major shoutout to Gilles Retsin for helping me pull this together. https://lnkd.in/eRTnbZPa
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Naresh Soni
We’re excited to share that our fund has invested in Cerebras Systems. Artificial intelligence is entering a phase where infrastructure matters as much as algorithms. As AI adoption accelerates across industries, the demand for scalable compute to train and run increasingly complex models is growing exponentially. Cerebras is building technology designed specifically for this new era of AI. Their breakthrough approach centers on wafer-scale computing — a radically different architecture built to handle large-scale AI workloads with greater efficiency and speed. Instead of stitching together thousands of smaller processors, Cerebras developed a single, massive AI processor designed to simplify how large models are trained and deployed. What impressed us most about Cerebras is their bold rethinking of AI compute architecture and their focus on solving one of the most important challenges in the AI ecosystem: enabling organizations to run large AI models faster and at scale. As AI moves from experimentation to mission-critical enterprise deployment, the infrastructure powering these systems will become increasingly important. We believe Cerebras is well positioned to play a meaningful role in shaping that future. We’re excited to support the team as they continue to push the boundaries of AI infrastructure. #AI #ArtificialIntelligence #DeepTech #Infrastructure #Investing
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