about 3 years ago, micro1 lost 60% of its revenue overnight and almost went bankrupt. today, i'm proud to share we've surpassed $1B annual run rate while remaining historically profitable. it’s been a special journey. we’re grateful for every struggle, moment, and person who has been part of it. we've taken a very untraditional path to get here. our core team is only ~180 people, spanning 14+ countries, and fully remote. many of our decisions sacrifice hundreds of millions of revenue and slow us down short term. but we believe they compound into advantages that are impossible to replicate long term. the long term is now. these are the 8 principles that made micro1 a leader in the data industry and will soon make us number one: 1.) human 1st AI: treat the tens of thousands of experts helping train models with absolute best-in-class care. our goal is to make AI training one of the largest, highest paying, and most enjoyable job sectors in the world. 2.) U.S. first: we refuse to work with adversarial nations, or export data that improves models against the interests of Americans. 3.) long-term research over short-term ARR: invest in deep research, products, and infrastructure for years from now, not just the next customer pipeline. 4.) proper incentives for intensely hard work: no arbitrary requirements like 996. inspire people to work extremely hard with outlier incentive structures instead of forcing weekend work. we’ve maintained close to 100% core team retention as a result. 5.) stay lean and global: we’ve reached $1B run rate with ~180 people, and intend to slow team growth significantly from here. exceptional talent is found around the world, and pedigree is the wrong thing to over-index on. 6.) execution alignment: company to retain a streamlined board so we can optimize for the next several decades, remain light-weight and dynamic, and take bold & calculated risks. 7.) abundant intelligence improvement: invest in building data generation models to make high-quality datasets and RL environments dramatically less expensive and more abundant. 8.) scale data on realism and horizon: realism brings the complexity of the real world into training models, while horizon extends how long models can work and how much complexity they can handle. both have enormous room to scale, and we’re pushing the limits of both. additionally: after surpassing $500M run rate this summer, we priced our Series B at a $4B valuation, alongside a ~$25M tender to give our early employees liquidity as we build for the long term. the round was led by Dream Ventures, a longtime supporter and one of our earliest investors, alongside Microsoft, Javelin, Flybridge, G Squared, Up Partners, and LG. we’re also grateful to be backed by incredible industry leaders, including Guodong Zhang (co-founder of xAI), Andy Fang (CTO of DoorDash), Igor Babuschkin (co-founder of xAI), Behnam Neyshabur (founder of Mirendil), Jerry Tworek (ex-VP of Research at OpenAI), and many more. data is on its way to becoming the largest industry humanity has ever seen, and we're certain this is just the beginning. best, Ali

Today we’re launching micro1’s PII transformation model, flow-transform 1.0, delivering frontier-level performance across detection, identity synthesis, and transformation of personally identifiable information. On PrivacyBench, our model reaches 96.0% F1, outperforming every detection baseline we tested, including Tonic Textual, Claude Opus 4.8, Sonnet 4.6, Microsoft Presidio, Haiku 4.5 and GLiNER2. Some of the most valuable training data for frontier AI models lives inside fully functioning companies. It captures years of real work across decisions, communications, tools, handoffs, exceptions and the relationships connecting them. The problem is that this data is also full of PII. Traditional redaction makes the data safe, but it also destroys the very workflows and relationships frontier models need to learn from. flow-transform 1.0 solves this by turning enterprise operational data into high-fidelity training data for frontier models by replacing real-world identities without flattening the reality the data captures.

deeply concerning that some American data companies are selling AI training data to labs in adversarial nations. this also includes operational data from U.S. businesses turned into AI training environments, and without telling the business owners. operational data captures years of how a company works, makes decisions and solves problems. when that knowledge becomes an RL environment, AI models practice those workflows and learn from the experience that business spent years building here in the U.S. signing a deal with an American company shouldn’t mean unknowingly helping train AI for a foreign adversary. at micro1 we only work with U.S. AI labs and our allies. we won’t ever sell proprietary American business knowledge (or any other data driving the frontier of AI) to adversarial nations.

Better Auth is joining Vercel! From the very beginning, this team has been my biggest inspiration and has always reflected many of the reasons I started working on Better Auth. I’m incredibly grateful to our community, our team, our investors - in particular @koomen and @arnavsahu341 from @peakxvpartners for believing in my vision and taking a chance on me. And thank you everyone @vercel that made this happen - I'm excited to to be building together!! I’ve shared some thoughts on the blog post linked Excited for what’s ahead ❤️ better-auth.com/blog/better-…