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\n\t\tOpinions expressed by Entrepreneur contributors are their own.\t<\/p>\n
Insurance companies used to spend months pricing disasters.\u00a0Earthian AI<\/u><\/a>\u00a0wants to do it in real time.\u00a0<\/p>\n The Amsterdam-based startup, founded by former Harvard researcher Shayan Shokri, is building what it calls a \u201cfinancial inference layer,\u201d an AI system designed to tell banks, insurers, and asset managers not just what\u2019s happening in the world, but also what those events are actually worth in dollars and their risk exposure.<\/p>\n And investors are paying attention.<\/p>\n On April 30,\u00a0Earthian<\/a>\u00a0announced a\u00a0<\/a>pre-seed raise\u00a0<\/u><\/a>at a<\/u><\/a>\u00a0$112 million valuation<\/u><\/a>\u00a0\u2014 structured as equity plus debt \u2014 with backing from Rabobank and NVIDIA\u2019s Inception program. The angel round also drew former executives from Goldman Sachs, Moody\u2019s, and Accenture.<\/p>\n \u201cFive Fortune 500 firms are using our risk models today, and we expect that to be 30 by 2027,\u201d Shokri said in a statement. \u201cThat kind of traction doesn\u2019t come from a good pitch deck. It comes from solving a problem these institutions have been trying to solve internally for years.\u201d\u00a0<\/p>\n The problem isn\u2019t hypothetical. Natural catastrophes caused\u00a0$107 billion in insured losses globally in 2025<\/u><\/a>, the sixth straight year that figure has exceeded $100 billion. The Los Angeles wildfires alone accounted for $40 billion. Add in geopolitical fragmentation, climate volatility, and AI-driven cyber threats, and the math is moving faster than the analysts trying to do it.\u00a0<\/p>\n Credit:\u00a0Earthian AI<\/em><\/p>\n That\u2019s where Earthian\u2019s positioning starts to land. While large language models dominate most public AI conversations, Earthian is focused on SLMs, or small language models, trained specifically for financial reasoning.\u00a0<\/p>\n \u201cA large language model can write you a sonnet, but it shouldn\u2019t be pricing your catastrophe exposure,\u201d Shokri said. \u201cOur small language models run faster, use less energy, and hold up better in regulated environments. They don\u2019t hallucinate on the kind of financial nuance that general AI tends to choke on because they were never trained to be generalists.\u201d\u00a0<\/p>\n The models may be small, but the intake is massive. Earthian\u2019s AI engine processes up to 2 billion data points per day, pulling from satellite imagery, SEC filings, regulatory updates, and corporate disclosures \u2014 a level of capacity that exceeds what even the largest insurers typically have in-house.<\/p>\n And risk modeling is just the entry point. A separate research initiative,\u00a0Project Alpha-Index<\/u><\/a>, explores what the company calls \u201cAI-native portfolios,\u201d models that continuously rebalance holdings across all 11 GICS sectors based on forward-looking risk reasoning, with the goal of outperforming traditional benchmark strategies like the S&P 500.<\/p>\n It\u2019s a direct shot at how Bloomberg, Moody\u2019s, and S&P Global have built their empires for decades: aggregate the data, sell it, repeat. Earthian is betting the next category belongs to whoever can interpret risk fastest.<\/p>\n Shokri isn\u2019t thinking small either. \u201cWe want to be worth $1 trillion within ten years,\u201d he told\u00a0FD<\/u><\/em><\/a>, pointing to Google and Nvidia as proof that markets nobody saw coming can reshape entire industries almost overnight.<\/p>\n That may sound enormous. But then again, pricing disasters in real time used to sound impossible too.<\/p>\n<\/p><\/div>\n Insurance companies used to spend months pricing disasters.\u00a0Earthian AI<\/u><\/a>\u00a0wants to do it in real time.\u00a0<\/p>\n The Amsterdam-based startup, founded by former Harvard researcher Shayan Shokri, is building what it calls a \u201cfinancial inference layer,\u201d an AI system designed to tell banks, insurers, and asset managers not just what\u2019s happening in the world, but also what those events are actually worth in dollars and their risk exposure.<\/p>\n And investors are paying attention.<\/p>\n<\/p><\/div>\n