Inferensys

Service

Enterprise Shadow AI Discovery and Inventory Service

Comprehensive network scanning and AI usage detection to build a real-time inventory of all sanctioned and unsanctioned AI tools, models, and endpoints across your enterprise, providing the foundational visibility required for governance.
Governance lead reviewing model governance framework on laptop, policy documents visible, executive office setup.

Comprehensive network scanning to build a real-time inventory of all sanctioned and unsanctioned AI tools and endpoints across your enterprise.

You can't govern, secure, or optimize what you don't know exists. Our discovery service provides the foundational visibility required for AI governance.

  • Automated Network & Endpoint Scanning: Continuously maps your environment using passive and active techniques to detect AI model endpoints, API calls to providers like OpenAI and Anthropic, and unauthorized SaaS integrations.
  • Real-Time Asset Inventory: Creates a single source of truth dashboard showing model names, versions, data flows, responsible teams, and associated risk scores.
  • Integration with Existing Stacks: Correlates findings with your SIEM, CMDB, and cloud billing data (AWS, Azure, GCP) for unified attribution and showback.
FROM DETECTION TO GOVERNANCE

Tangible Outcomes of Complete AI Visibility

Our Enterprise Shadow AI Discovery and Inventory Service delivers more than a simple list of tools. It provides the foundational intelligence required to secure your data, optimize costs, and enforce compliance across all AI deployments.

01

Real-Time AI Asset Inventory

Automated network scanning and API log analysis build a continuously updated, centralized registry of every sanctioned and unsanctioned AI model, endpoint, and service in use across your hybrid cloud environment. This eliminates governance blind spots and provides a single source of truth for your AI estate.

100%
Network Coverage
< 24 hours
Initial Inventory
03

Multi-Cloud Cost Attribution & Showback

Specialized auditing of AWS, Azure, and GCP bills and API logs to identify, categorize, and attribute all AI service consumption. This enables precise showback to business units, eliminates wasteful spending on duplicate tools, and supports FinOps initiatives for AI cloud consumption.

30%
Avg. Cost Savings
Granular
Department Attribution
04

Proactive Data Exfiltration Prevention

Deploy network-level and endpoint monitoring to detect and alert on API calls to unauthorized external AI providers (OpenAI, Anthropic, etc.). This prevents sensitive PII, intellectual property, and regulated data from leaving your environment through unvetted SaaS integrations.

Real-Time
Alerts
DLP Integration
Supported
05

Automated Compliance Evidence Generation

Automatically generate audit trails and reports mapping AI data flows to specific regulatory articles (GDPR, HIPAA, EU AI Act). Our service provides the technical evidence required to demonstrate compliance during audits and reduces manual reporting overhead by security teams.

ISO/IEC 42001
Alignment
Automated
Reporting
06

Integration with SIEM & SOAR Platforms

Seamlessly integrate discovered AI risks and policy violations into your existing Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) workflows. This unifies AI security alerts with your broader enterprise incident response.

Splunk, Sentinel
SIEM Ready
Automated
Ticket Creation
Structured Implementation

Phased Delivery for Rapid, Actionable Results

Our service delivers immediate visibility and ongoing governance through a clear, phased approach. This table outlines the key deliverables and capabilities activated at each stage of the engagement.

Capability & DeliverablesPhase 1: Discovery & Inventory (Weeks 1-4)Phase 2: Risk Assessment & Policy (Weeks 5-8)Phase 3: Ongoing Governance & Integration (Week 9+)

Enterprise-Wide AI Asset Inventory

Real-Time Shadow AI Detection Dashboard

Risk Scoring & Financial Exposure Analysis

Prioritized Remediation Roadmap

Custom AI Usage Policy Development

Integration with SIEM/SOAR & Existing IAM

Automated Compliance Reporting (GDPR, HIPAA)

Continuous Monitoring & Alerting SLA

Basic

Standard

Advanced (99.9% Uptime)

Typical Engagement Scope

Initial 90-day audit

Policy & integration design

Managed service or annual retainer

HIGH-VISIBILITY SECTORS

Industries Where Shadow AI Poses the Greatest Risk

Unsanctioned AI tools create unique compliance and security vulnerabilities in heavily regulated industries. Our discovery service provides the foundational visibility needed to quantify and mitigate these risks before they result in data breaches or regulatory fines.

01

Financial Services & Banking

Shadow AI in trading algorithms, fraud detection, or customer chatbots can lead to model manipulation, biased lending decisions, and catastrophic data leakage of PII and transaction data. Our inventory maps all AI endpoints to meet FINRA, SOX, and PCI-DSS audit requirements.

Learn more about our Financial Services Algorithmic AI and Risk Modeling services for sanctioned deployments.

70%
of firms have unsanctioned AI
< 48 hrs
to initial risk report
02

Healthcare & Life Sciences

Unauthorized AI analyzing PHI, medical imaging, or genomic data violates HIPAA and introduces life-critical diagnostic errors. Our service discovers AI tools accessing EHRs and research data, preventing multi-million dollar compliance penalties and protecting patient safety.

For compliant AI development, see our Healthcare Clinical Decision Support and Ambient AI solutions.

$50K+
per HIPAA violation
100%
PHI flow mapping
03

Legal & Professional Services

Teams using unsanctioned LLMs for contract review or legal research risk exposing privileged client communications, creating malpractice liability and violating attorney-client privilege. We identify all AI interacting with case files and sensitive documents.

Explore our Legal and Compliance Workflow Automation for governed AI tools.

500+
AI endpoints scanned
24/7
monitoring & alerting
04

Defense & Government Contracting

Shadow AI in supply chain logistics, document analysis, or communications creates severe national security risks and ITAR/CMMC compliance failures. Our air-gapped discovery deployment identifies AI tools across classified and unclassified networks without external data exposure.

For secure AI development, review our Defense and National Intelligence AI capabilities.

Air-Gapped
deployment option
CMMC L3
compatible
05

Manufacturing & Critical Infrastructure

Unauthorized AI in SCADA systems, predictive maintenance, or quality control can be manipulated to cause physical damage, production halts, and safety incidents. We map AI integrations across OT and IT networks to secure Industry 4.0 environments.

For sanctioned industrial AI, see Smart Manufacturing and Industrial Copilot Integration.

OT/IT
unified visibility
Real-time
anomaly detection
06

Technology & SaaS Companies

Engineers using unsanctioned AI coding assistants risk leaking proprietary source code and intellectual property. Our service detects AI usage in CI/CD pipelines and developer environments, enforcing code security policies before merge.

Implement governance with our AI Model Registry and Lifecycle Governance service.

99%
API call detection
Git Integration
for pre-commit hooks
Get Clear Answers

Frequently Asked Questions on Shadow AI Discovery

Common questions from CTOs and security leaders about implementing a comprehensive shadow AI discovery program.

Our standard deployment delivers a comprehensive initial inventory within 2-4 weeks. This includes agentless network scanning, cloud API log analysis, and endpoint discovery. Continuous monitoring is established from day one, with the inventory updating in real-time as new AI tools are detected.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.