GC AI went from $1M to $10.8M in ARR in under a year.
It did it in the most crowded corner of AI. In 2026 Harvey raised at an $11B valuation, Legora closed a $550M Series D at $5.55B, and Milan’s Lexroom raised $50M eight months after its Series A.
The gap? Almost every legal AI company was building for law firms, which sell legal hours to clients.
GC AI built for
in-house lawyers: the legal team inside a company, like the general counsel at Vercel or Liquid Death.
They are growing more than twice as fast as lawyers in firms and governments.
23% average monthly revenue growth in 2025
A $60M Series B at a $555M valuation, with only $73M raised in total
2,100 legal teams as customers, from Lockheed Martin to Liquid Death
One third of its 125 employees are lawyers
Its founder? Cecilia Ziniti spent 20 years as a lawyer inside tech companies, from Yahoo to Amazon Alexa and Replit. She had never founded a company and never written code.
📚 In this newsletter, we break down how GC AI found its first customers by teaching, built a product lawyers trust, and grew 10x in under a year!
Inside you will find:
How 20 Years as an In-House Lawyer Became GC AI’s Unfair AdvantageSee how a career from Yahoo to Alexa and Replit turned into a ready-made product spec.Path to the First Customers: How Teaching 507 Lawyers Built the Pipeline Before the ProductFind out how paid prompting classes brought 2,000+ companies into the pipeline before the sales team existed.Path to $1M: How GC AI Turned Legal Judgment Into a Daily Product and Reached 350+ CustomersLearn which features made lawyers trust the answers, and how that turned into 95% retention.Path to $10.8M: How Trust and Speed Took GC AI Past $10.8M ARRSee how solutions attorneys, free courses and general counsel investors cut the enterprise sales cycle.Path to $20M: How GC AI Plans to Hold Its Ground Against Harvey, Legora and MicrosoftFind out where GC AI stands at an estimated $20M ARR, and who is coming for its customers.5 Lessons to Steal From GC AI’s PlaybookTake the five moves and apply them to your own vertical AI startup.
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