Investor thesis

AI agents need a new access-control layer.

AgentFort is the access-control layer for the AI-agent era. It secures enterprise agents before they touch real systems: runtime identity, hidden credentials, job-scoped temporary access, policy enforcement, sandboxing, prompt-injection defense, egress control, and audit evidence.

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Why now Agents are becoming enterprise operators.

They are moving from chat into APIs, browsers, SaaS tools, code, and sensitive workflows faster than existing security controls were designed to govern.

Why AgentFort Enterprises need an agent control plane, not another IAM rule.

AgentFort combines agent identity, short-lived access, hidden credentials, runtime protection, prompt-injection defense, egress limits, and audit evidence.

Why this founder Built security automation at Amazon.

Founded and led AI security automation products and teams inside Amazon, with 12 years across appsec, identity, payments, patents, and a master's degree in Artificial Intelligence.

The problem

Enterprises cannot give agents broad credentials.

Over-permissioned access creates new identity risks, data exposure, compliance gaps, and insider-risk scenarios.

Our solution

AgentFort gives every agent controlled, temporary access.

We provide runtime identity, broker short-lived access, keep credentials hidden, enforce policy by job, constrain runtime and egress, and produce audit evidence.

Our wedge

Start with high-risk agent workflows.

Coding agents, browser agents, internal copilots, customer-support agents, and regulated-data workflows where security needs proof before production adoption.

Why I can build this

Founded, built, and led security automation products and teams inside Amazon across application security, identity, payments, and enterprise-scale systems.
Created Design Inspector and Deep Threat Modeler to turn architecture, codebase, data-flow, and dependency signals into security reasoning.
Worked directly on access boundaries, least privilege, service-to-service authentication, regulated data, and production security review.
Master's degree in Artificial Intelligence, applied to automated threat modeling, secure design analysis, and now agent identity and access control.

Issued patents in security automation and design analysis.

Patent No. Title Focus area
12,174,963 Automated selection of secure design patterns Secure design automation
12,019,742 Automated threat modeling using application relationships Threat modeling automation
11,531,763 Automated code generation using analysis of design diagrams Design analysis and code generation
11,507,655 Automatic and predictive source code generation Predictive code generation
10,860,295 Automated detection of ambiguities in software design diagrams Design quality and ambiguity detection