Y Combinator

AI-Native Compliance Infrastructure

Y Combinator is soliciting founder applications for companies that replace fragmented, manual compliance infrastructure with AI-native systems capable of consolidating regulatory tools and reducing reliance on specialized legal personnel. These ventures aim to solve the inefficiencies of state-by-state regulatory patchwork by automating monitoring, anomaly detection, and audit trails to provide finance teams with real-time global visibility. As such solutions become essential enterprise infrastructure for global expansion, successful applicants will be expected to redefine compliance operations through a default AI operating mode rather than simple process automation.

Proving You’re Human

Following a $25 million fraud involving deepfake avatars impersonating corporate executives, industry experts identify the collapse of traditional human verification as a critical vulnerability across digital communications. Strategic initiatives are now prioritizing the reconstruction of an internet trust layer capable of authenticating identities in video calls, messages, and transactions without compromising user privacy. The entity that successfully builds this scalable verification infrastructure is projected to become the mandatory standard for financial institutions and social platforms over the next decade.

What Big Tech Missed And How Startups Can Still Win

Alexandre LeBrun, Zuckerberg, Jan, Alex

Ami Labs is raising approximately one billion euros in seed funding to develop foundational world models that train on sensory data rather than text, addressing the limitations of current large language models for robotics applications. Co-founded by Alex K. and Yann LeCun following their shared history at Meta and various startups, the Paris-based company aims to build general-purpose robots capable of operating safely in open environments by solving the compute bottlenecks and latency issues inherent in existing vision-language-action architectures. While the venture tackles the high capital demands of securing thousands of GPUs and top-tier talent, it operates under a strict strategic constraint where failure to deliver visible progress within two years could render the company unsustainable due to the intense external expectations created by the massive funding round.

Why Physical AI Is the Next Platform Shift

Eric Landau, Francois Chollet

Anchored, founded by former quantitative trader Eric Landau, constructs the data layer for physical AI by managing petabytes of multimodal data to power robotics and autonomous systems. After pivoting from healthcare vision to broader industrial applications, the company established a production-ready facility in the Bay Area and refined its sales culture through iterative hiring challenges. With the post-ChatGPT market accelerating demand for specialized physical AI infrastructure, Anchored now leads a crowded sector by offering scalable data collection that moves clients from proof-of-concept to enterprise production.

Data for the Real World

Emerging companies like Gecko Robotics and Sorcer are leveraging falling sensor costs and advanced foundation models to collect dense physical world data from inaccessible environments, addressing the limitations of current human-centric remote sensing. This shift enables industries such as energy, agriculture, and logistics to transition from relying on intuition-based modeling to controlling complex systems, opening pathways for transformative applications like hurricane steering and global cooling. The initiative actively seeks strategic partnerships with firms developing similar physical data collection methodologies to accelerate market growth in these critical sectors.

New Operating Systems for the Physical World

A new software operating system addresses the stagnation in physical-world management by unifying AI agents, robots, and human workers into a single platform. This architecture shifts the industry value proposition from simple visibility to the direct coordination of heterogeneous labor, targeting the massive economic leverage inherent in industries where labor costs vastly exceed software spending. By capturing continuous, real-time data from mixed-field operations, the system establishes a unique data moat designed to train superior AI models and optimize safety and reliability in ways incumbent solutions cannot match.

What Top AI Labs Are Really Doing With Observability

Olivier Pomel, Alexi

Founded by IBM veterans Olivier Pomel and Alexi Laurent, Datadog disrupted the monitoring industry by merging Dev and Ops into a single platform, overcoming initial Y Combinator rejections and regional venture capital biases to achieve a 2019 IPO. Under a leadership philosophy that prioritizes direct customer engagement over written values, the company has expanded its product suite to serve top AI firms while executing a radical shift where engineers will primarily automate code generation within two quarters. This strategic pivot aims to drastically increase development velocity and reorganize the company around smaller, high-autonomy teams, even as it navigates post-lockup valuation volatility and the rapid evolution of AI-driven observability.

He Built the World's #1 Open-Source Coding Agent

Jay V, Gary Tan, Mark Mandelmann, Seth Vargoevic, Frank, Dax, Dylan Patel, Soyal, PG, Jay Poldinger

OpenCode, a sixteen-year-old platform founded by Jay Poldinger and Frank, has grown to 13 million monthly active users and processes 7 trillion daily tokens by serving as a neutral model harness that bypasses vendor lock-in. The company's strategy of supporting over 70 open-source models, which became critical after Anthropic restricted open usage, generated $160,000 in monthly subscription revenue and an estimated $33 million in inference revenue as of June. With significant adoption in China, Brazil, and the United States, OpenCode validates its product-market fit through enterprise organizations that proactively seek security agreements to integrate its agent loops into internal workflows.

How Photoroom Trained Themselves To Dream Bigger

Gary Tan, Elliot

PhotoRoom, the largest Y Combinator company headquartered in Europe, leveraged a strategic pivot to e-commerce photography to achieve 300 million downloads and serve major clients like Amazon and Uber. Its founders attribute this exponential growth to a cultural shift fostered by YC, which replaced European risk aversion with a "failure-safe" mindset that treats a billion-dollar valuation as an attainable target. By enforcing English-only offices, prioritizing deep vertical focus, and utilizing aggressive resource constraints, the company instilled a mandatory ambition across its team to drive rapid scaling and execution speed.

The Best Time to Build in Crypto

Despite bear market headwinds, Y Combinator is accelerating its crypto investment strategy by targeting infrastructure and non-crypto fintechs that are already integrating stablecoins and blockchain rails. This approach leverages the sector's shift toward organic building, with current portfolio expansions focusing on Latin American and Indian capital flows while filtering out speculative competition. YC aims to publish further insights on these institutional trends shortly before its fall batch applications close on July 27th.

AI for the Aging Population

Facing a projected surge to 20% of the U.S. population over age 65 by 2030 alongside a critical caregiver deficit, emerging technologies are addressing the urgent need for better senior support. While existing consumer voice assistants often frustrate older adults, new AI-driven solutions are introducing natural conversational interfaces, safety monitoring, and robotics to enable independent living. These innovations aim to bridge the gap for the 53 million unpaid family caregivers and tap into the world's largest underserved market by streamlining care coordination and emergency response.

Scientists Are Built for Startups

Arvind Veluvali, Ayman Saleh, Dima Yanovsky

The speaker leverages their experience engineering fungus-based materials and simulating the NASA Perseverance rover to argue that scientists, particularly those from structured space agencies, possess the ideal mindset for startup entrepreneurship. Contrasting NASA's rigid, decade-long project lifecycles with the high-pressure, iterative environment of seed-stage ventures, the speaker demonstrates that technical feasibility and the willingness to conduct long-term experiments are more critical than formal business training. Ultimately, the presentation posits that researchers accustomed to managing massive-scale contractor coordination and undefined success metrics are uniquely prepared to lead new ventures despite the inherent risks.

AI-Powered Consumer Products for 1 Billion People

Positioning artificial intelligence as the most significant platform shift since the web era, the analysis highlights a critical window where AI agents have achieved sufficient human-like capability to support viable consumer products. While unit economics currently require approximately $1,000 per user monthly, rapid cost reductions of 10x annually are projected to trigger a widespread "consumer moment" where early entrants can secure permanent market dominance across sectors like automation, health, and finance. The initiative explicitly seeks builders to develop applications targeting a one-billion-user market before the competitive landscape solidifies.

How Supabase Became One Of The Fastest Growing DevTool Companies In The World

Paul Copplestone

Supabase founder Paul Copplestone recently secured a $500 million round at a valuation exceeding $10 billion, propelling the company to decacorn status with a 10 million developer base driven largely by AI agents launching 60-90% of new databases. The fully distributed organization leverages its open-source PostgreSQL strategy and a shift toward Infrastructure as Code to achieve exponential usage growth, reducing time-to-value from minutes to seconds while bypassing traditional marketing channels. Moving beyond standard user interfaces, Supabase is now building self-driving database capabilities and "Infrastructure for Platforms" to support enterprise labs managing millions of ephemeral instances autonomously.

Compute at Sea

Amidst critical shortages of onshore compute capacity, electricity, and land, the industry faces significant regulatory delays and community opposition to new data centers. To address these constraints, a proposed strategy involves deploying standardized "compute flotillas" that leverage the ocean's vast surface area, abundant solar energy, and natural cooling properties to create a unified global cloud. Investors are currently soliciting applications from founders building this offshore infrastructure to overcome existing terrestrial bottlenecks.