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

Comprehensive network scanning to build a real-time inventory of all sanctioned and unsanctioned AI tools and endpoints across your enterprise.
- Automated Network & Endpoint Scanning: Continuously maps your environment using passive and active techniques to detect AI model endpoints, API calls to providers like
OpenAIandAnthropic, 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.
This service directly addresses the critical first step in AI Security Posture Management (AI-SPM): establishing an accurate, continuously updated asset register. It transforms shadow AI from an invisible liability into a managed asset, enabling informed decisions on AI-SPM integration and risk quantification.
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.
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.
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.
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.
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.
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.
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 & Deliverables | Phase 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 |
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.
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.
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.
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.
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.
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.
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.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
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Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.

Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.

Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
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.

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.
Partnered with leading AI, data, and software stack.
How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
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Pick the right approach
We define what needs search, automation, or product integration.
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Build the first useful version
We implement the part that proves the value first.
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Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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