Nortal

Which of your low-risk findings would an attacker use first? Glassworks, our agentic code review is built to answer that. Our specialist AI agents hunt for vulnerabilities in your code and the logic beneath it, then trace which ones chain into a real attack path, so you know which weakness to fix first.

Your AI policy probably took months to agree on. A code review shouldn’t make you start over. Glassworks, our agentic code review runs on the model you already trust, wherever you want it to run. The harness only reads your code and never changes it. You also decide how far we go: a findings list your engineers act on, or our engineers fix the vulnerabilities as well. Point us at the system you’d start with. We’ll tell you what an attacker could reach, and what to fix first.

Your team can’t fix every weakness at once. What matters is which ones an attacker could actually use. Glassworks, our agentic code review answers that. AI verifiers test each finding against your code’s logic and rate it by how easy it is to exploit. We trace how small weaknesses chain into real attack paths, so a finding that looks minor on its own gets the attention it needs. Every confirmed vulnerability comes with a recommended fix. See how we trace an attack path through your code.

The cheapest time to fix a weakness is before anyone has used it. Glassworks, our agentic code review helps you get there first. Our specialist AI agents hunt for vulnerabilities, AI verifiers check every finding, and we trace how small weaknesses chain into real attack paths. Break one link and the path closes, so your engineers spend their time on the fixes that remove the most risk. See how a review works and what you get at the end.

We tested Glassworks on 20 public code repositories with known, documented vulnerabilities. They found 70% on the first pass and 95% after nine. Every extra pass found vulnerabilities the earlier ones had missed. That’s why our agents read your code several times, and why AI verifiers check every finding before it reaches your report. The benchmark is public and the models may have seen it in training, so we report these figures as a conservative floor rather than a guarantee for a given codebase. Our agentic code review, trained to hunt, not just to scan.

Your AI policy probably took months to agree on. A code review shouldn’t make you start over. Glassworks, our agentic code review runs on the model you already trust, wherever you want it to run. The harness only reads your code and never changes it. You also decide how far we go: a findings list your engineers act on, or our engineers fix the vulnerabilities as well. Point us at the system you’d start with. We’ll tell you what an attacker could reach, and what to fix first.