Build or Buy AI Pentesting? What the POC Doesn’t Tell You
Watch Synack customer Dow discuss why a successful AI pentesting POC is only the beginning, and what it takes to deliver reliable, validated security outcomes at enterprise scale.
Every new frontier model release brings fresh pressure to build internal AI pentesting tools. Your engineers are capable, the APIs are available and the first proof of concept looks genuinely impressive. So why buy? It is a fair question, and it deserves a better answer than a sales pitch.
Watch Dan Lacher, Dow's Cybersecurity Engineering Team Leader, Mark Kuhr, Synack's Co-Founder & CTO, and Tim Nordvedt, Solutions Architect at Synack, discuss both sides of the decision. Hear their perspectives on the real engineering tradeoffs, the costs teams often overlook and what it takes to operationalize AI pentesting at scale.
- Why a working POC is not the same as a dependable security control, and what bridges the gap
- The hidden costs that can derail internal builds, including token spend, model drift, staffing and compliance gaps
- Why false positives in AI pentesting are an architectural problem, not simply a tuning problem
- What human oversight looks like in practice for autonomous offensive security tooling
- The questions to ask before committing significant engineering resources, and where building internally may still make sense
WATCH THE RECORDING
AI is changing the buy vs. build debate for pentesting
Watch the 30-minute webinar to learn how Dow chose Synack over building its own AI pentesting engine with Sara AI Pentesting.
