Carmen Li, CEO of Silicon Data: $5M+ Building the World's First GPU Compute Risk Management Platform

Carmen Li spent decades in financial services across trading floors and data companies before spotting a massive inefficiency in the AI/compute economy. After managing global data partnerships at Bloomberg, she witnessed AI startups struggling with unpredictable compute costs that could swing their margins from healthy profits to devastating losses overnight. Drawing parallels to how airlines hedge oil prices through futures markets, Carmen realized that compute—despite being one of the fastest-growing commodities—lacked basic risk management tools. Within months of leaving Bloomberg, she built Silicon Data into the world's first GPU compute risk management platform, raising $5.7M without ever creating a pitch deck and publishing the industry's first GPU compute index on Bloomberg Terminal.

Topics Discussed:

• The systemic problem of compute cost volatility destroying AI company margins
• Why compute lacks the risk management tools available in every other commodity market
• Building the world's first GPU compute index and benchmarking service
• Raising venture capital without pitch decks through product-first demonstrations
• Operating as a solo non-technical founder leading a team of engineers
• The unique buyer dynamics when selling to CTOs, portfolio managers, and AI researchers simultaneously

GTM Lessons For B2B Founders:

• Price on value, not cost, and let customer conversations reshape your understanding: Carmen admits that every client conversation changes her valuation of the product's impact, typically making it bigger than initially thought. She prices based on the value delivered rather than cost structure. B2B founders should remain flexible in their value proposition and pricing as they learn more about customer impact through direct engagement.
• Product demonstrations beat pitch decks for technical buyers: Carmen raised $5.7M without ever creating a pitch deck, instead letting prospects interact directly with her product and writing a simple memo. For technical products solving complex problems, demonstrating actual capabilities often proves more effective than polished presentations. B2B founders should prioritize building working products over perfecting sales materials.
• Embrace being the "dumbest person in the room" for learning velocity: Carmen describes consistently being the least technical person in rooms full of CTOs, AI researchers, and GPU experts, but leverages this as a learning advantage. She asks hard questions and co-creates products on the fly based on these conversations. B2B founders should view knowledge gaps as opportunities for rapid learning rather than weaknesses to hide.
• Target systemic problems that span multiple sophisticated buyer types: Silicon Data serves everyone from chip designers to hedge funds to AI companies, requiring Carmen to handle technical GPU questions, financial modeling queries, and AI workflow concerns in single meetings. This breadth creates natural expansion opportunities and defensibility. B2B founders should look for problems that affect multiple stakeholder types within their target market.
• Leverage unique background intersections to spot obvious-but-overlooked opportunities: Carmen's combination of financial services expertise and data company experience let her quickly identify that compute needed the same risk management tools available in every other commodity market. The solution was "extremely intuitive" to her but invisible to others. B2B founders should examine how their unique background combinations reveal opportunities others might miss.

 

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