The AI Security Gap Nobody's Staffed For

AI adoption outpaced AI governance two years ago. For mid-market companies without dedicated AI security teams, the question isn't whether something will go wrong — it's whether you'll know when it does. We're the firm closing that gap.

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The Problem

The Governance Gap: How AI Deployment Outran Security

The AI governance gap isn't a technology problem. It's an organizational one.

Most mid-market companies — the 50-to-500-employee firms moving fastest on AI adoption — have no one whose job it is to secure their AI systems. The CISO, if there is one, owns infrastructure and endpoints. The engineering team owns velocity. The AI agents being deployed into production sit between these two mandates, governed by neither.

The result is predictable: customer-facing AI agents with access to sensitive data, no output guardrails, and no monitoring. Internal agents making decisions with no audit trail. Prompt injection vulnerabilities that wouldn't survive a weekend on a bug bounty program — if anyone thought to test for them. This isn't negligence. It's a structural gap. And it's everywhere.

How We're Different

We Build What We Secure. That Changes Everything.

The conventional approach to AI security treats it as an extension of application security. Run a scan. Check a compliance box. Move on. This fundamentally misunderstands the problem.

AI agents aren't static applications. They reason, they access tools, they make decisions based on context that changes with every interaction. Securing them requires understanding how they think — which requires building them. This is the core thesis behind SecureAgent's approach: the people best equipped to find vulnerabilities in AI systems are the people who build AI systems and encounter those vulnerabilities firsthand.

We call this Builder's Eye Security, and it's not a framework or a methodology. It's a perspective. When our team audits an AI agent, they're drawing on direct experience building the same architectures, using the same orchestration patterns, making the same tradeoffs your team made last sprint. They're not referencing a knowledge base. They're referencing last Tuesday's production deployment.

Services

From Assessment to Ongoing Protection: A Structured Approach

$5–15K

AI Security Audit

A comprehensive assessment of your AI attack surface — the kind of assessment that most firms aren't equipped to perform, because most firms haven't built the systems they're assessing.

$15–25K

Security Sprint

Embeds our engineers with your team to remediate critical findings and establish defensible architectures.

$5–10K/mo

Managed Security

Continuous oversight for teams shipping AI on an ongoing basis.

Each engagement begins the same way: a conversation about what you've built, what you're building next, and what keeps you up at night. No questionnaires. No sales engineers. Engineers who build AI, talking to engineers who build AI.

Social Proof

Trusted by Teams Shipping AI at Scale

We had three customer-facing agents in production with zero security review. SecureAgent found critical vulnerabilities in the first 48 hours.

Engineering Lead · Series B Fintech

They didn't just find the problems — they understood why we'd made those tradeoffs. That's what made the remediation actually stick.

VP of Engineering · Healthcare SaaS

The managed engagement gives us confidence to ship faster. We have a security team for AI without having to build one internally.

CTO · AI-Native Startup

Start With Clarity

Every engagement starts with a conversation, not a contract.