AI is already running inside your business. Are you running it?
IronGate brings the visibility, accountability, and enforcement that enterprise AI environments demand — so your organization can move forward with confidence, not exposure.
of enterprises cannot fully account for AI activity in production
3
questions every board should be able to answer about its AI — and usually cannot
0
tolerance among regulators for organizations that cannot reconstruct AI behavior under scrutiny
The Governance Gap
Most enterprises cannot answer three basic questions about their AI governance.
01Who authorized this AI action, and who is accountable for it?
02What data did it touch, and what systems did it cross?
03Can you reconstruct exactly what happened, when regulators ask?
"If your answer to any of those questions is 'we're not sure,' the risk is already live inside your environment."
AI agents are making decisions across your enterprise right now — touching sensitive data, triggering workflows, crossing systems. The technology has outpaced the governance frameworks designed to contain it. That gap represents real exposure: regulatory, operational, and reputational. IronGate exists to close it, before it surfaces at the worst possible moment.
What We Do For You
Control and accountability, built into your AI environment.
This is not a policy document or a compliance checklist. It is an active governance layer that runs alongside your AI — in production, in real time.
01 — Visibility
See Everything Your AI Is Doing — Right Now
Real-time monitoring across every AI agent in your environment. No more blind spots between adoption and accountability. Know what is running, where it is running, and what it is touching.
02 — Attribution
Every Action Tied to an Accountable Identity
AI without attribution is a liability. IronGate connects every AI action to the identity behind it — so responsibility is never ambiguous, and your audit trail is always intact.
03 — Auditability
Reconstruct Any AI Behavior, On Demand
When a board member asks a question or a regulator requests documentation, the answer is already there. Reconstruct the full history of any AI interaction, at any point in time.
04 — Enforcement
Set the Boundaries. We Make Sure AI Stays Within Them.
Define guardrails and access controls across your AI systems. IronGate enforces those boundaries at runtime — not retroactively, after exposure has already occurred.
05 — Cost Attribution
Know Exactly What AI Is Costing You
AI spend is growing faster than anyone's ability to account for it. IronGate breaks down costs by team, workflow, and AI system — giving finance and operations the data they actually need.
06 — Governance Readiness
Satisfy Boards and Regulators Without Slowing Innovation
Responsible AI adoption does not mean slow AI adoption. IronGate gives your leadership the evidence they need to move forward with confidence — and the documentation to back it up.
Free Assessment
How governed is your AI? Find out.
Your AI Governance Scorecard
Answer eight questions about your AI environment. In under three minutes, you will have a clear picture of where you stand — and where you are exposed.
No proprietary information required
Instant results, no sales call needed
Specific recommendations by risk area
Built on the same framework IronGate uses with enterprise clients
AI Governance Quick Assessment
QUESTION 01 OF 08
What type of AI system is your organization primarily using or evaluating?
QUESTION 02 OF 08
Can your organization identify which users or roles are behind each AI interaction?
QUESTION 03 OF 08
If asked today, could you reconstruct the full history of a specific AI interaction from three months ago?
QUESTION 04 OF 08
Does your organization have documented policies governing what AI systems can and cannot access?
QUESTION 05 OF 08
Has your board or executive leadership formally addressed AI governance risk?
QUESTION 06 OF 08
Do you know what data your AI systems are accessing or generating?
QUESTION 07 OF 08
Can you attribute AI spend accurately by department, team, or business function?
QUESTION 08 OF 08
In the event of an AI-related incident, does your organization have a response plan?
AI governance does not look the same in every environment. Here is where we see it matter most — and what we are doing about it.
Federal Agencies
Governing AI at the Federal Level
Federal agencies face AI governance requirements unlike any other sector. Executive orders on AI safety, Office of Management and Budget directives, and the evolving FedRAMP authorization process are all placing new demands on how agencies deploy and oversee AI systems. IronGate works with federal technology and security leaders to bring the visibility and accountability infrastructure that these environments require — before the auditors arrive asking for it. IronGate's partner platform is targeting FedRAMP High authorization in Summer 2026, supporting agencies that require the highest level of cloud security assurance.
USE CASE 01
AI Agent Accountability in Mission-Critical Workflows
Federal agencies are deploying AI agents inside sensitive workflows — procurement, benefits adjudication, intelligence analysis. IronGate establishes attribution and audit trails for every AI action, ensuring that accountability does not disappear into the model.
USE CASE 02
Zero-Trust AI Access Control for Sensitive Systems
Zero-trust architecture applies to AI just as it does to human users. IronGate enforces granular access policies for AI systems touching classified or sensitive data — so no AI agent accesses more than it is authorized to, and every access event is logged.
USE CASE 03
OMB AI Governance Compliance Readiness
OMB Memorandum M-24-10 establishes AI governance requirements for federal agencies. IronGate maps its governance layer directly to these requirements — giving agencies the documentation and evidence base they need for compliance reviews and inspector general assessments.
USE CASE 04
AI Cost Visibility Across Agency Programs
AI spending is growing inside federal budgets faster than financial teams can track it. IronGate provides cost attribution by program, system, and user group — giving agency CFOs and CIOs the visibility they need to manage AI expenditure as a line item, not a mystery.
State agencies, municipal governments, and public universities are adopting AI at a pace that outstrips their governance frameworks. State CIOs, Departments of Transportation, DMVs, and public school systems are all facing the same fundamental challenge: AI is making decisions that affect citizens, and there is no clear accountability structure in place. IronGate works with SLED leaders to establish the governance infrastructure that responsible public sector AI requires — before a constituent complaint or a legislative inquiry forces the issue.
USE CASE 01
AI in Public-Facing Services
From benefits processing to DMV services, AI is touching citizen-facing workflows in state and local government. IronGate ensures those interactions are auditable, attributable, and defensible when constituents, legislators, or media come asking for answers.
USE CASE 02
Student Data Protection in AI-Enabled Education
Public universities and K-12 systems are deploying AI tools that touch student records and learning data. FERPA obligations do not disappear because the system is AI-driven. IronGate brings governance controls that protect student data and keep institutions compliant.
USE CASE 03
Infrastructure and Emergency Management AI
AI systems that support traffic management, emergency dispatch, or public safety operations carry governance requirements that go beyond typical enterprise concerns. IronGate provides the oversight layer that high-stakes public sector AI demands.
USE CASE 04
Board and Legislative Accountability for AI
State legislators and school boards are increasingly asking questions about AI in public institutions — and getting insufficient answers. IronGate gives public sector leaders the documentation and reporting they need to respond with confidence.
Publicly listed companies face AI governance pressure from multiple directions simultaneously: SEC disclosure expectations, board fiduciary obligations, activist shareholders, and an increasingly AI-aware audit community. The question is no longer whether AI governance will be scrutinized — it is whether your organization will have the evidence base ready when it is. IronGate works with public company technology and legal teams to build the governance layer that stands up to that scrutiny, and to make sure the board can answer the questions that are coming.
USE CASE 01
SEC AI Disclosure Readiness
The SEC has signaled clear expectations around material AI risk disclosure. IronGate provides the documentation infrastructure that makes those disclosures accurate, defensible, and consistent — so legal and finance teams are not scrambling at reporting time.
USE CASE 02
AI Risk in Board Reporting
Boards of public companies are asking about AI risk. Most management teams do not have good answers. IronGate builds the reporting layer that translates operational AI activity into board-level risk language — giving directors the visibility they have a fiduciary obligation to have.
USE CASE 03
AI Auditability for External Auditors
External auditors are beginning to test AI systems as part of broader control assessments. IronGate ensures that AI behavior is reconstructable, attributable, and documented — so audit findings do not surface control failures that leadership was not aware of.
USE CASE 04
AI Cost Attribution for Financial Reporting
AI spend is becoming a material line item for public companies. IronGate breaks it down by business unit, function, and system — giving finance the visibility to capitalize, expense, or allocate AI costs accurately in financial statements.
Private companies — from PE-backed mid-market businesses to large private enterprises — are adopting AI faster than any governance framework is evolving to contain it. The absence of public reporting requirements does not reduce exposure; it just means the gaps are less visible until something goes wrong. Portfolio companies, in particular, carry AI governance risk that aggregates across the holding company's book. IronGate works with private company leadership, private equity sponsors, and operating partners to establish governance that holds up under diligence, protects enterprise value, and prepares organizations for whatever comes next.
USE CASE 01
AI Governance in Private Equity Portfolio Companies
PE sponsors are beginning to include AI governance in operating playbooks. IronGate works with portfolio operations teams to deploy governance infrastructure across multiple companies efficiently — creating a consistent standard that protects enterprise value across the book.
USE CASE 02
Pre-Transaction AI Due Diligence Readiness
Buyers are beginning to ask hard questions about AI in diligence. Sellers who cannot answer them are leaving value on the table or accepting liability carve-outs. IronGate prepares private companies for AI-related diligence by building the documentation and governance evidence base before the process begins.
USE CASE 03
AI Agent Risk in Customer-Facing Products
Private mid-market companies are embedding AI agents into customer-facing products and internal workflows alike. When those agents behave unexpectedly, the consequences — customer loss, legal exposure, reputational damage — fall on the organization. IronGate provides the runtime enforcement that catches issues before they become incidents.
USE CASE 04
Operationalizing AI Governance as a Growth Lever
For growth-stage private companies, demonstrating mature AI governance is increasingly a competitive differentiator in enterprise sales. IronGate helps fast-moving organizations build governance structures that support — rather than slow — commercial momentum.
Kyle spent eight years at PwC learning precisely how enterprises account for what they cannot see and what that exposure costs when it surfaces. That same discipline now shapes his approach to AI. He founded IronGate because the gap between AI adoption and AI accountability is widening faster than most boards realize. As AI becomes embedded across enterprise workflows, the questions are no longer about capability. They are about control, attribution, and what happens when regulators come asking. Kyle built IronGate to give organizations the answers before the questions become urgent.
Twenty years of building enterprise technology revenue gives Rahul a particular lens on what actually works in the field versus what sounds good in a presentation. He has led go-to-market, presales, and delivery across supply chain infrastructure, enterprise integration, and B2B SaaS from global consultancies to venture-backed startups. He has seen how organizations adopt technology and where governance breaks down under real conditions. At IronGate, he brings the commercial architecture and operator's instinct to help C-suite leaders build the internal case for AI governance and make sure deployment translates into real accountability, not just a policy document on a shelf.
