Shrav Mehta, Founder and CEO of Secureframe – Interview Series

Shrav Mehta, Founder and CEO of Secureframe, is an entrepreneur and technology leader focused on simplifying cybersecurity and regulatory compliance through automation. He founded Secureframe in 2020 after building experience across engineering and growth roles at fast-growing startups including Pilot, Scale AI, Lob, and Hired. Earlier in his career, he founded and scaled a portfolio of successful Android applications and games that reached millions of users. Under his leadership, Secureframe has become one of the leading security compliance automation platforms, helping organizations streamline complex certification processes while earning backing from top venture firms including Kleiner Perkins, Accomplice, Gradient Ventures, Base10 Partners, and others.

Secureframe is a cybersecurity and compliance automation platform that enables organizations to achieve and continuously maintain industry-leading security and privacy certifications with significantly less manual effort. The platform automates evidence collection, continuous monitoring, security awareness training, vendor risk management, and audit preparation through hundreds of integrations with cloud providers, identity platforms, development tools, and business applications. Supporting frameworks including SOC 2, ISO 27001, HIPAA, PCI DSS, NIST, CMMC, FedRAMP, and GDPR, Secureframe helps companies strengthen their security posture while accelerating enterprise sales by making compliance faster, more scalable, and easier to maintain throughout the year.

Before founding Secureframe, you worked across engineering, marketing, and growth roles at companies like Pilot, Scale AI, Lob, and Hired, and even built Android apps that reached millions of users. What specific experiences convinced you that security compliance was broken enough to dedicate a company to solving it?

It all really started with my own frustration. Throughout my career, I watched super sharp engineering teams grind to a halt the moment a major enterprise customer handed them a security questionnaire or required a SOC 2 report. Cybersecurity compliance became a hindrance to business growth, instead of an accelerator.

I started asking people in my network whether they’d want tools to automate this. Many said yes, but I wasn’t sure how serious they were until one person called me back a month later asking where the product was. I quit my job that week and officially started Secureframe. By the time we had an MVP, more than 40 companies were on our waitlist.

Today, we help thousands of companies navigate, maintain, and scale this critical work. It’s deeply rewarding to see how our platform removes friction, turning a historic bottleneck into a competitive accelerator for our customers.

Your recent cybersecurity summit found that six in ten security professionals believe they have critical threat intelligence gaps. Why do you think so many organizations still struggle to understand their true risk exposure despite spending heavily on cybersecurity?

One thing we’ve consistently seen working with thousands of organizations is that most security teams don’t lack data, they lack context. They’re getting alerts from dozens of tools, but they’re still struggling to answer basic questions like where sensitive data lives, who has access to it, and what their specific risks look like. In fact, our polling showed that while 60% consume standard government feeds, only 29% participate in industry-specific ISAC sharing. Government alerts are valuable, but by the time one lands in your inbox, the threat has often already evolved.

The deeper problem is that networks expand faster than the inventory of what’s on them. If you don’t have a clear, up-to-date picture of where your sensitive data lives and who touches it, adding another security tool won’t save you.

You’ve described a future where cybersecurity becomes a form of “symmetric AI warfare,” with both attackers and defenders using increasingly autonomous systems. How does this fundamentally change the way enterprise security teams need to operate?

When AI can run most of an operation autonomously, reconnaissance, exploitation, and lateral movement with minimal human involvement, a human analyst opening a ticket at 9 AM for an alert that was sent at 2 AM has already lost the battle.

The security professional’s role shifts from active responder to orchestrator: setting policy, validating the integrity of defensive systems, and eliminating blind spots rather than triaging an endless queue of low-level alerts.

During our summit, former NSA Cybersecurity Director Rob Joyce put it plainly: “There’s no going back to the pre-AI threat model. The decisions you make about your defense are decisions about the new normal. We’re not preparing for a possible future.”

If AI allows attackers to reduce breakout times from hours to seconds, what are the biggest weaknesses in today’s traditional security and compliance models that make organizations vulnerable?

The biggest weakness is point-in-time, static, or manual validation. Traditional compliance relies on compiling documentation once a year to prove a control was working on a specific date. That model falls apart when software is being generated, iterated, and deployed continuously. A snapshot taken last quarter may not tell you much about your security posture today. That’s why frameworks like FedRAMP are moving toward automated and persistent validation.

A second major weakness is how flat many enterprise networks still are. When sensitive operational systems sit on the same network as everyday corporate tools, a single compromised account can become a much bigger problem very quickly.

Many organizations still treat compliance as a periodic audit exercise. Why do you believe that mindset is becoming dangerous in an era where threats evolve continuously?

Because adversaries don’t attack on your audit schedule. They exploit the gap between how your systems looked during an assessment and how they’re actually configured three months later. Configurations drift, employees come and go, new software gets integrated; all of this creates exposure that a once-a-year review will never catch.

Compliance frameworks like SOC 2 or CMMC are meant to define an operational floor, not a finish line. Treating them as a periodic project is how companies end up running into trouble in reassessments or, worse, in security incidents between assessment cycles.

What does an AI-driven continuous protection model actually look like in practice, and how does it differ from the security operations centers most enterprises rely on today?

Today, security teams spend the majority of their time manually triaging a flood of alerts, investigating incidents one by one, and collecting evidence for audits through screenshots, spreadsheets, and point-in-time documentation.

An AI-driven model inverts that. Instead of analysts chasing alerts, automated systems continuously monitor behavioral patterns across data, identities, and infrastructure. When something drifts from an established baseline, automated workflows close the gap immediately rather than waiting for a human to notice and act.

AI can also take over the documentation burden entirely, generating and maintaining risk assessments, control evidence, and compliance records based on the live state of the environment rather than a snapshot taken before an audit. The security team shifts from doing that work to overseeing the systems that do it.

Nation-state cyber threats are becoming more sophisticated and better funded. What capabilities do you believe enterprises must develop over the next three years to remain resilient against these types of adversaries?

Precise data scoping, automated supply chain verification, and behavioral-based security architectures.

Nation-state actors are excellent at blending in using stolen credentials and legitimate system tools to move through networks without triggering conventional alerts. Catching that kind of activity requires monitoring patterns of behavior, not just scanning for known malware signatures.

On the supply chain side, our survey data showed that 58% of security practitioners cite third-party vendor risk as their single largest unresolved gap. Manually reviewing vendor spreadsheets once a year while sophisticated actors are targeting your suppliers is not a real defense.

Finally, keeping sensitive environments isolated from the rest of your corporate network dramatically reduces your exposure. Organizations that controlled their compliance costs most effectively did so by limiting how far their sensitive data could spread in the first place.

As AI becomes more capable, do you expect the cybersecurity skills gap to widen or narrow? Which security roles are likely to become more important, and which may become increasingly automated?

I think the cybersecurity skills gap will widen in complexity but narrow in volume. AI will handle the routine repetitive work that has historically consumed junior analysts like log reviews, basic documentation, and straightforward patching. That frees up capacity, but it also raises the bar for what skilled practitioners need to know.

The roles that will matter most going forward are those focused on architecture and governance: professionals who can design resilient systems, assess the security of AI pipelines themselves, and interpret a fast-shifting regulatory environment.

Secureframe has expanded from compliance automation into broader security monitoring and AI-powered remediation. Where do you see the line between governance, risk management, compliance, and active cyber defense beginning to blur?

Those functions were always artificially separated. In practice, they’re all expressions of the same question: can you demonstrate that your systems are doing what you say they’re doing?

When an automated system closes a security gap in real time, it has simultaneously updated your risk posture, logged a governance event, and generated compliance evidence. The shift we’re seeing is from point-in-time compliance to continuous trust, and AI is increasingly how that trust gets validated. Not just maintained.

Looking ahead, do you believe we are approaching a point where AI systems will be responsible for defending critical infrastructure with minimal human intervention, or will human judgment remain the ultimate safeguard against large-scale cyber attacks?

It will always require both, and leadership culture will determine how well either element works.

Former CISA CIO Bob Costello made this point at our summit when he described how SolarWinds (SWI ) changed the federal conversation: moving from treating compliance as a checkbox exercise toward genuinely understanding the real-time risk posture of an entire environment. That shift in mindset is what separates resilient organizations from vulnerable ones.

The companies that come out ahead know where their sensitive data lives before anyone asks, have replaced manual evidence collection with automated systems, and have built a culture where security behaviors are embedded in daily work rather than reserved for annual training. For those operating in regulated or high-stakes environments, the window for gradual modernization is closing.

Thank you for the great interview, readers who wish to learn more should visit Secureframe.