Have you ever looked at how security gets done and thought, “I know AI could do this better”? Yeah, us too. That’s why we built Maze.
Our CTO and co-founder, Santiago, digs into some of the most interesting, and hardest, problems we solved between a working MVP and the Maze that runs across millions of vulnerabilities weekly:
- Building an accurate context layer that feeds the agents
- Understanding the difference between using one big prompt vs many specialized ones
- Selecting the best model for the job
- Designing an architecture that balances accuracy, efficiency, and cost
It took us over a year, and a lot of engineering creativity, to achieve results that are scalable, accurate, consistent, and won’t break the bank. Come hear about what we learned.
Speakers
Co-Founder and CTO of Maze, the agentic reasoning platform for vulnerability management, where he leads engineering. He brings years of hands-on experience in the field and spent 15+ years building and scaling software in senior technical roles at Amazon, S&P Global, Monad Inc, and Jungle Robotics. He pairs deep engineering expertise with a track record of turning complex security challenges into products teams can use.
