Services / AI Security
AI Security and Automation Consulting
Two tracks, one practice. Secure the AI your teams are already using, and build automated security workflows that reduce analyst workload with production-tested agentic pipelines.
Review an AI Security InitiativeTwo tracks, one practice
Most companies need both. AI governance addresses the risk of AI adoption. Security automation addresses the operational cost of running a security program. Both are now inseparable from modern security leadership.
AI Governance
Your teams are already using AI tools. The question is whether you know which ones, what data they are touching, and what controls are in place. Without governance, every new AI adoption is a security review that did not happen.
- +AI use-case and data risk review
- +Shadow AI discovery and approved tool inventory
- +Acceptable use policy and guardrails
- +MCP server and agentic tool security review
- +LLM and agent red teaming (prompt injection, tool abuse)
Security Automation
Agentic workflows that reduce analyst workload on repeatable tasks: alert triage, compliance evidence collection, vulnerability prioritization, and threat intelligence enrichment. Built on production-tested pipelines, not demos.
- +Alert triage automation (GuardDuty, EDR, SIEM)
- +Compliance evidence workflow automation
- +Vulnerability prioritization and outreach pipelines
- +Supply chain and threat intelligence monitoring
- +Custom security agent design and implementation
Why this matters now
AI adoption inside companies is outpacing security team capacity. Browser extensions, coding assistants, AI API integrations, and agentic tools are being connected to internal systems and sensitive data without the vetting that would be applied to any other third-party service.
At the same time, security teams are being asked to do more with the same headcount. Automation is not optional anymore. The question is whether it gets built thoughtfully with the right failure modes in mind, or bolted on reactively after an incident.
This practice is built on production experience, not theory. The workflows and governance frameworks come from operating real AI security pipelines at scale.
Who this is for
- +Companies actively adopting AI tools who need governance before an incident forces the conversation
- +Security teams spending too much time on manual triage and evidence collection
- +Engineering teams building AI products who need a security review of their agent architecture
- +CISOs and security leaders evaluating MCP server deployments and agentic tool risk
How it starts
A free 30-minute scoping call
We identify whether you need governance, automation, or both, and deliver a fixed-price proposal within 24 hours.
Book a Free CallCommon questions
What is AI security governance?
AI security governance is the set of policies, controls, and review processes that determine how your organization adopts and operates AI tools safely. It covers acceptable use, data handling, model risk, third-party AI service vetting, and monitoring for misuse or prompt injection attacks.
What is an MCP security review?
The Model Context Protocol (MCP) is a standard for connecting AI agents to external tools and data sources. An MCP security review evaluates the servers your agents can reach, the data they can access, and the controls in place to prevent prompt injection, tool abuse, or unauthorized data access.
Can AI actually automate security operations?
Yes, for specific well-defined tasks. Alert triage, evidence collection for compliance, vulnerability prioritization, and phishing analysis are all areas where agentic workflows can reduce analyst workload meaningfully. The key is scoping to tasks where the failure mode is an analyst reviewing a false positive, not missing a real incident.
How do I know if my team is using AI tools that create security risk?
Start with DNS monitoring for known AI platform domains and review browser extension inventories for AI coding assistants. A more systematic approach involves a Shadow AI discovery exercise that maps tools in use against your approved list and evaluates each for data handling risk.