AI Security · Agentic SOC · AI Governance & Visibility

AI Is Now Your Largest
Unmanaged Attack Surface.

Your teams are shipping AI apps, wiring up agents with production access, and adopting tools faster than security can track. We secure what you build, stand up the agentic SOC that defends it, and give you governance over every model and agent — so your team can operate with confidence.

45-minute working session with a senior AI security engineer. No sales deck. You leave with a prioritized risk list.

3
Security pillars, one accountable partner
Minutes
To triage & close routine incidents, not hours in a queue
Days
From risk review to a prioritized roadmap
Full
AI inventory — including shadow AI and unmanaged agents

AI adoption is outrunning the controls that are supposed to govern it.

Developers embed LLMs into production apps. Teams grant agents standing access to data and infrastructure. Business units buy AI tools on a credit card. Most security programs have no inventory of any of it, no policy enforcement on any of it, and no detection built for how these systems actually get attacked.

You cannot secure, monitor, or govern what you have never inventoried.

Shadow AI: 14 SaaS tools sending data to third-party LLM APIs — unsanctioned Finding 1
Agent "deploy-bot" holds standing AdministratorAccess in production Finding 2
Customer-facing chatbot deployed with no prompt-injection guardrails Finding 3
Vector store with PII embeddings reachable from the public internet Finding 4
Prompt injection exfiltrating secrets through an internal MCP server Finding 5

Three pillars. One accountable security partner.

Most vendors sell one product and leave the integration to you. We own the outcome across the full lifecycle of your AI systems — from the code your teams write to the agents defending them to the governance your board asks about.

Pillar 1
1

Secure AI Development & AI Workloads

We harden the AI apps, agents, models, and pipelines your teams build and run — threat modeling for LLM and agent architectures, prompt-injection and data-exfiltration testing, model and MCP supply-chain review, and least-privilege boundaries for every agent with production access.

Pillar 2
2

Agentic SOC & AI-Powered Security Operations

AI agents detect, triage, investigate, and remediate threats under a deterministic control plane that returns binary, policy-backed verdicts — not probabilistic guesses. Every decision is logged, auditable, and reviewable, with humans in the loop on anything high-risk.

Pillar 3
3

AI Visibility, Governance & Cost Control

We discover every AI system in use — sanctioned and shadow — and build the inventory of models, agents, vendors, and data flows behind it. Then we enforce policy, monitor usage and cost, quantify risk, and produce the evidence your auditors and board require.

What changes after you engage us.

📉

Measurable reduction in AI attack surface

Over-permissioned agents are scoped down, exposed models are locked, and injection paths are closed. We track exposure before and after, so the reduction is a number you can show, not a claim.

Threats remediated at machine speed

The agentic SOC investigates and closes routine incidents in minutes under deterministic policy — freeing your analysts for the decisions that actually need a human.

👁️

A complete, living AI inventory

Every model, agent, vendor, and shadow-AI tool in one governed view — the single source of truth every audit, budget review, and board question depends on.

🛡️

Governance that enforces itself

Policy is applied at runtime, not written in a document nobody reads. Violations are caught and blocked instead of discovered after an incident.

🧾

Audit-ready compliance evidence

Decisions, controls, and outcomes map to NIST AI RMF, ISO 42001, SOC 2, and your internal frameworks — generated continuously, not reconstructed the week before an audit.

💸

AI spend under control

Usage and cost visibility across every model and vendor exposes waste and runaway consumption before it reaches finance as a surprise.

Machine-speed attacks require machine-speed defense — under human control.

AI-driven attacks already operate at a scale humans cannot match

Automated reconnaissance, exploit generation, and lateral movement move faster than any manual SOC. Defending against them requires agents that operate at the same speed.

Agents alone are not enough — they drift toward the answer you want

LLM-based agents are optimized to be agreeable. In security there is only good or bad. A deterministic control plane converts agent output into binary, policy-backed verdicts you can defend.

One partner across all three pillars removes the integration gap

Point tools leave the seams between build, defend, and govern for you to fill. We own those seams, which is where most real-world breaches happen.

We work in your environment, not from a slide deck

Senior engineers implement inside your stack — cloud, CI/CD, SIEM, identity, and ticketing — so controls actually ship instead of becoming a backlog.

🤖
Agent Layer

AI agents ingest signal from your existing vendors and detect, triage, and investigate at machine speed across your entire environment.


⚖️
Deterministic Control Plane

Every agent action is evaluated against your policy and a rule set built from real threat response. Same input, same verdict, every time — fully logged.


📊
Governance & Evidence

Every decision feeds a queryable audit trail and a live AI inventory, turning day-to-day operations into the compliance evidence your board and auditors require.

Senior operators, not a reseller with a demo.

Deterministic

Not another LLM wrapper

Our Stathera control plane returns binary verdicts governed by explicit policy and rules — auditable and repeatable, immune to prompt drift and sycophancy.

In-environment

We implement, we don't advise and leave

Engagements are run by senior engineers working directly in your cloud, CI/CD, and SOC tooling until controls are live and verified.

Framework-mapped

Evidence auditors accept

Controls and outcomes map to NIST AI RMF, ISO/IEC 42001, SOC 2, and your internal requirements — produced as a by-product of operations.

The questions security leaders ask us first.

Why act on this now instead of next budget cycle?

Your AI attack surface is already live and already being probed — shadow AI tools, agents with standing production access, and LLM features shipped without a threat model. Every quarter you wait, the inventory you eventually have to secure gets larger and the first incident gets more likely. The Risk Review exists so you can act on evidence now instead of after a breach.

Why should we trust Cloud Security Pros over a larger vendor?

We are senior AI security operators who implement inside your environment, not a reseller running a demo. Our Stathera control plane is deterministic — it returns binary, policy-backed verdicts rather than probabilistic LLM output — and every decision is logged and auditable. You can verify our work; you don't have to take it on faith.

Why this approach instead of the point tools we already have?

Point tools secure one slice — a scanner, an EDR, a CSPM — and leave the seams between building AI, defending it, and governing it for you to integrate. Those seams are where breaches happen. We own all three pillars end to end and orchestrate the agents your existing vendors already ship.

Why not just keep managing AI risk the way we do today?

Most current programs have no AI inventory, no runtime policy enforcement, and detection built for a pre-AI threat model. That gap does not shrink on its own — AI adoption inside your organization is widening it every week. The status quo is a growing, unmeasured liability.

What exactly happens in the AI Security Risk Review?

A 45-minute working session with a senior engineer. We walk your AI footprint across the three pillars, identify the highest-exposure gaps, and hand you a prioritized risk list you keep whether or not you engage us further. No sales deck, no obligation.

What environments and tools do you support?

AWS, Azure, and Google Cloud, including hybrid and multi-cloud. We orchestrate agents and signal from major SIEM, EDR, CNAPP, and identity platforms, and integrate with Jira, ServiceNow, and Slack.

Find out what your AI is exposing — before an attacker does.

Book a 45-minute AI Security Risk Review with a senior engineer. We map your AI footprint across all three pillars and hand you a prioritized risk list you keep, whether or not you work with us.

Schedule an AI Security Risk Review

No sales deck · No obligation · Findings are yours to keep

What you get: Prioritized AI Security Risk List

Schedule Your AI Security Risk Review

Tell us about your environment so the engineer on your call arrives prepared. We reply within one business day to confirm a time. No sales deck.