AI Productivity For Enterprises

Measure the Productivity of Your AI Workforce

Shadow AI isn’t a future risk to plan for. It’s already operating inside your environment, accessing data, making decisions, and creating liability with every action nobody is watching. ANTS finds every agent, governs every decision, and gives your security team full control before a regulator or an incident does it for you.

3× more agents than IT knows

47 agents discovered in a first ANTS scan

0 endpoint agents required to get full visibility

SHADOW AI RISK

Shadow AI creates risk when it operates
outside the controls of security teams

A shadow IT app stores data in the wrong place. A shadow AI agent makes decisions in the wrong place, with zero oversight and liability that compounds with every action.

The policy gap

Most organisations don’t struggle because they lack an AI policy. They struggle because that policy was never designed to govern systems that deploy in twenty minutes, access data across multiple systems, and make thousands of decisions before anyone looks at a report. By the time a periodic review runs, the damage is already done.

Where shadow AI breaks control

Deployment gap - A capable AI agent can be built and deployed in an afternoon with no IT, no procurement, no oversight. Shadow IT took weeks to spin up. Shadow AI takes minutes.
Data access depth - Unlike a shadow file share, an AI agent actively queries systems, synthesises data, and acts on inferences. Its data footprint is almost always wider than intended.
Decision liability - Unreviewed, unlogged, ungoverned decisions in a regulated environment are not an oversight. Under EU AI Act, HIPAA, and equivalent standards, they are a violation.

RUNTIME ANALYTICS

Token, Cost & Behavior Intelligence

Bloomberg-grade telemetry for the AI runtime - every prompt, every model call, every dollar accounted for.

Discover

Find every agent including the ones nobody told you about.

ANTS operates at the API and SDK layer where agents actually run, not where they were supposed to be registered. It detects every active agent in your environment regardless of whether IT was ever told about it. No endpoint agents. No manual inventory process. No dependency on teams reporting their own deployments.

● Continuous real-time discovery, not a periodic audit
● Detects sanctioned agents, shadow agents, and embedded vendor AI
● Surfaces agents accessing data outside their original scope

What a first scan typically finds

● 3× more agents than the approved inventory — confirmed across every ANTS discovery deployment
● Scope violations — agents accessing data well beyond their original approval
● Ghost agents — at least one “decommissioned” agent still actively running
● Vendor-embedded AI — activated inside approved software updates with no separate AI review

Shadow AI categories

Category 01: The well-intentioned build

A team deploys a capable agent. It works. They share it. Within two weeks it’s processing hundreds of records a day with zero security review. Nobody did anything wrong, but it is operating at scale on customer data with no governance layer.

Category 02: The forgotten deployment

An agent was approved 18 months ago. The team moved on. The vendor pushed model updates. It no longer does what it was approved to do. This is the most common form of shadow AI in regulated industries: authorised systems that drift while oversight fails to keep pace.

Category 03: The embedded vendor agent

Your CRM ships a routine update. Buried inside: a new AI feature, live the moment IT approved the update. No AI review. No data access assessment. Most organisations have no mechanism to catch it.

RUNTIME ORCHESTRATION

Govern AI Behavior in Production

A control plane between every agent and every model. Policies enforced at runtime, not in a spreadsheet.

Step 01

Agent discovered & inventoried

Name, framework, data access, and owner recorded in real time.

Step 02

Risk tier assigned automatically

Low / Medium / High by data type, decision consequence, and regulatory exposure.

Step 03

Governance controls applied proportionally

Not every agent carries the same risk. Controls match the tier.

Step 04

Live risk map, not a spreadsheet

Discovery tells you what is running. Classification tells you what it means.

RUNTIME SECURITY

Stop threats before they produce consequences

Security requires intervention before an agent decision executes, before data leaves, and before liability is created.

ANTS enforces at the runtime layer: every agent decision is evaluated against policy before it produces an output.

● PII and PHI blocked before it exits the system
● Unsafe actions prevented before they execute
● Jailbreak and prompt injection detection
● Behavioural drift alerts — before drift becomes an incident
● Kill switches for immediate agent quarantine
● Every enforcement event logged with full decision context

Live threat intercept

● PII exposure — blocked
● Prompt injection — detected & flagged
● Unsafe action — prevented
● Behavioural drift — alerted
● Rogue agent — quarantined (0 incidents passed through · all enforcement logged)

COMPLIANCE PROOF

Audit-ready evidence for shadow AI control

Every enforcement event, policy decision, and risk tier is captured in a structured, exportable audit trail.

Compliance frameworks covered

● EU AI Act
● HIPAA
● ISO/IEC 42001
● SOC 2 Type II
● GDPR
● NIST AI RMF
● CCPA
● California AI Regs

Audit evidence sample

● Agent #0047 — discovered & logged
● Risk tier assigned — High
● Enforcement event — recorded
● Evidence stored — exportable
● Full trail ready for audit on demand

Be audit-ready before the regulator calls

Every agent ANTS discovers, every enforcement action it takes, and every policy it applies is captured continuously in a structured, exportable audit trail. When a regulator asks for evidence of AI oversight, the answer takes minutes, not weeks of manual assembly.

● Continuous evidence collection — starts from the first scan
● Structured, exportable audit trails — timestamped per decision
● Mapped to EU AI Act, HIPAA, ISO 42001 obligations
● Shared system of record across security, legal, and compliance

AI SECURITY MODEL

The four-layer AI security model built for runtime control

Built for the layer where AI decisions actually happen, not the layer where they were registered.

Continuous discovery

Real-time inventory of every agent updated as new ones appear. A live picture, not a quarterly audit.

Inventory & classification

Risk level, data scope, and regulatory category automatically assigned. Governing a risk landscape, not a name list.

Runtime monitoring & enforcement

Guardrails at the decision point. Block, flag, escalate, quarantine before consequences, not after them.

Governance integration

Feeds directly into your compliance program, risk reviews, audit evidence, incident response, and board reporting.

REGULATED INDUSTRIES

Built for regulated and fast-moving industries

Defensible runtime AI security for industries that cannot wait for governance to catch up.

FinTech

Credit, claims & customer data — Every AI decision touching customer financial data carries regulatory liability. ANTS provides the runtime layer that makes these deployments defensible with evidence that holds up in an audit, not just in a policy document.

Healthcare

Clinical AI & PHI protection — PHI exposure through an unmonitored clinical agent is not a near-miss as it is a HIPAA incident. ANTS detects and blocks PHI exfiltration at the runtime layer, before it leaves the system.

IT Consultancy

Client environment visibility — Running a discovery scan before a governance engagement starts reveals the real scope of shadow AI in client environments as typically far more than any interview-based assessment surfaces.

Finance & Enterprise

Scale without the incident — The organisations that scale AI without a governance crisis are not moving slowly. They built the security and discovery layer before the agent fleet grew large enough to become ungovernable.

OPERATIONAL INTELLIGENCE

Built for the People Accountable for AI

Designed with CIOs, CISOs and Heads of AI deploying real agents at real scale.

Runtime security

Stop threats before they produce consequences.

Detection without enforcement is monitoring. Security requires the ability to intervene before the decision executes, before the data leaves, before the liability is created. ANTS enforces at the runtime layer: every agent decision evaluated against policy before it produces an output.

● PII and PHI blocked before it exits the system
● Unsafe actions prevented before they execute
● Jailbreak and prompt injection detection
● Behavioural drift alerts — before drift becomes an incident
● Kill switches for immediate agent quarantine
● Every enforcement event logged with full decision context