The honest answer is: partially
In 2026, a security engineer can point a frontier AI model at a SAST finding, give it access to a GitHub repository and a Jira board, and watch it trace a call graph, identify the code owner, draft a fix, and create a ticket. For a single vulnerability, this is genuinely impressive, and Seemplicity uses AI to do exactly this, at scale.
But investigating one finding and running a remediation program are fundamentally different problems. This datasheet explains exactly where AI helps, where it hits a wall, and what it would actually cost to build the rest yourself.
What AI Does Well
Tracing reachability:
is the vulnerable code actually in the execution path?
Assessing blast radius
and business criticality of the affected asset.
Identifying code ownership
via git blame, contributor history, and project structure.
Generating fix recommendations:
a code diff, step-by-step instructions, and an effort estimate.
Routing a fix-ready ticket
to the right project with the right priority and SLA.
