Pixee is the agentic security engineering platform your stack has been missing. We integrate across the SDLC to eliminate false positives, trace real exploitability, and auto-fix true vulnerabilities. Enterprise compliant, context-aware, and scanner agnostic.
Trusted by security teams at regulated enterprises
Companies average 100,000+ findings in backlog, take weeks to remediate issues, and spend all of their time on triage. The issue is that nothing has reliably turned findings into fixes at scale.
The rise of AI coding agents has made the problem worse. More code, more dependencies, more vulnerabilities, faster speed. Traditional AppSec wasn’t built for this world. Pixee is.
AI coding assistants changed development. Now security needs to change too. Pixee deploys specialized agents across the SDLC, connected by a shared context graph. Two capabilities are production-proven today. Three more are in development.
Agents review architecture and requirements for security implications before code is written. Threat surfaces, auth gaps, and data flow risks caught at design.
Security-focused AI participates in pull requests, learns your team’s patterns, and provides specific guidance, not just flags.
The resolution engine. Exploitability analysis separates real findings from noise by proving what’s actually exploitable in your environment, not just reachable. For real findings, fixes match your conventions, libraries, and validation patterns. Connect your scanner, see fixes in hours, watch developers merge them.
Backlog reduction in organized campaigns. Instead of drowning in 100,000 findings, run targeted campaigns (“eliminate all critical SQLi this quarter”) with fixes prioritized by risk. Progress tracking built in. 100+ fixes merged in week one is typical.
When the next critical CVE drops, assess blast radius across your entire estate and push fixes to every affected repository. Response time from weeks to hours.
All agents share a context graph that learns your conventions, policies, and risk tolerance. Every triage decision and every merged fix feeds back in. Month 1 is good. Month 6 is measurably better.
Your scanners flag thousands of findings. Most aren’t exploitable in your environment. Pixee’s exploitability analysis evaluates security controls, auth boundaries, and deployment context, not just reachability. 2,000 alerts become 50 real findings, each with evidence.
“This code path is behind 3 auth layers, only reachable via localhost. Not exploitable.” That’s the output — a technical proof, not a risk score. Your team stops triaging noise and starts fixing what’s real.
Generic AI says “use parameterized queries.” Pixee says “use your existing SafeQueryBuilder class on line 47 that handles your DB-specific escaping patterns.”
That difference — knowing your libraries, your patterns, your validation logic — is why developers merge Pixee fixes at 76% and reject generic patches 80% of the time. Pixee handles the research and first draft. Your developers make the final call.
Pixee integrates with Snyk, Checkmarx, Veracode, Fortify, SonarQube, Semgrep, CodeQL, and more. Every major SCM: GitHub, GitLab, Bitbucket, Azure DevOps. Self-hosted, cloud, or air-gapped. Bring your own model with Azure OpenAI.
Your existing scanner investment becomes more valuable, not redundant. Scanners find. Pixee fixes. No vendor lock-in. No rip-and-replace.
“We connected our Checkmarx instance on Monday. By Friday, developers had merged 47 fixes without a single escalation to our security team. That backlog had been sitting there for two years.”
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