Y Combinator invests in 70 agentic AI startups for 2025 batch
Y Combinator's Spring 2025 batch includes 70 agentic AI startups, each receiving $500k. Leadership changes see Dalton Caldwell and Michael Seibel step back while Jon Xu and Andrew Miklas become general partners.
Y Combinator’s Spring 2025 accelerator batch features 70 startups focused on agentic AI, with each receiving $500,000 in funding. The three-month program continues to be a launchpad for innovative AI ventures.
Leadership Changes at Y Combinator
- Dalton Caldwell, former managing partner, transitions to partner emeritus after 12+ years and 25 batches. He cofounds Standard Capital, an AI-native Series A firm.
- Michael Seibel, another longtime partner, also stepped back earlier this year.
- Jon Xu and Andrew Miklas were promoted to general partners in May, now overseeing founder support across batches.
Notable Startups in the Batch
- Cohesive: An agentic CRM for blue-collar businesses (janitorial, landscaping, etc.), automating lead generation and service scheduling.
- Docket: An AI agent for web testing, founded by ex-Citadel and Stripe engineers.
- Daxa: An AI tool by ex-Google executive Ananth Kashyap, monitoring user behavior for product improvements.
- PrismAI: Identifies issues via session replays, founded by a former Palantir/AWS engineer.
- VoiceOS: Voice AI for high-volume hiring, shortening recruitment cycles.
- Kirana AI: AI store manager for theft detection and inventory management.
- Sava: Robotics for sheet metal manufacturing, reducing iteration time.
- Aegis: Automates insurance denial appeals for healthcare providers.
- Cascade Space: Lunar/deep space communications system by a SpaceX alum.
Broader Context
- YC has funded 5,000+ companies since 2005, with a combined valuation exceeding $800 billion.
- Recently, YC accused Google of monopolistic practices in an antitrust filing.
- India is seeing similar accelerators like Together Fund and Lossfunk supporting AI startups.
Image: Agencies
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Dr. Sarah Chen
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A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.