How it works
Seezo Everywhere
Traditional SDLC
Agentic SDLC
Traditional design-stage review: the developer's design document goes to a Security Architect for manual review.
Blog
Built for both AppSec and Engineering teams
Perspectives from Seezo leadership on what design-stage security looks like when AI agents write the code.
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By the Numbers
The volume of AI-generated code is sharply increasing while the time to release is plummeting. Agentic pentesting models are getting very good at finding novel vulnerabilities in code. Embedding security in the AI-SDLC is our path forward.
42%
of all committed code is now written by AI, per Sonar's State of Code survey
Developers expect that share to reach 65% by 2027 — and only 48% always verify AI output before committing.
Seezo's Approach
Assessment and validate run inside the agent itself, so review scales with every line the agent writes, not with how many people are on the security team.
70%
shorter product development cycles with AI end to end, per McKinsey
6-9 month builds roughly compress to 2 weeks.
Seezo's Approach
Seezo skills are embedded in coding agents, meeting developers where they are, ensuring that products are secure by design.
86%
of vulnerabilities in production-scale code found by AI agents at DARPA's AIxCC
Found across 54M lines of code and patched in 45 minutes on average. Attackers run the same playbook.
Seezo's Approach
AI that finds vulnerabilities this fast will be pointed at your code too. Seezo builds security in up front: threat model at design time, code validated against it before shipping.
Telemetry
Know what ran, by whom, and when
Security teams get full visibility into what skills fired and when. Know when to step in and get auditors the data they need
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Frequently Asked Questions
Everything you need to know about the Seezo AI Plugin and how it fits into your workflow.



