Services
Shadow AI Detection and Security Posture Management (AI-SPM)
Shadow AI Detection and Security Posture Management (AI-SPM)
Enterprise network mapping and monitoring to detect, manage, and secure unsanctioned AI deployments created by individual teams, addressing governance blind spots that introduce data leakage risks. Sub-services include unsanctioned AI usage monitoring, enterprise AI-SPM integration, shadow AI risk assessment for financial services, and built-in Copilot fencing policies.
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.
AI Security Posture Management (AI-SPM) Integration
Implementation and configuration of dedicated AI-SPM platforms (like Wiz, Laminar, or Palo Alto) to centralize policy enforcement, risk scoring, and compliance monitoring for all AI assets, moving from detection to active management.
Shadow AI Risk Assessment and Quantification
Technical evaluation of discovered shadow AI deployments to quantify data leakage, compliance, and operational risks, providing CTOs with a prioritized, evidence-based remediation roadmap and financial exposure analysis.
Multi-Cloud AI Service Consumption Auditing
Specialized auditing of cloud provider bills (AWS, Azure, GCP) and API logs to identify and attribute unsanctioned AI service usage, enabling showback, cost optimization, and policy violation detection across hybrid environments.
API Call Monitoring for Unauthorized AI Integrations
Deployment of network-level and endpoint monitoring to detect and alert on API calls to external AI providers (OpenAI, Anthropic, etc.), preventing sensitive data exfiltration through unvetted integrations and SaaS applications.
AI Copilot and Assistant Usage Fencing
Development of technical guardrails and data loss prevention (DLP) policies for AI copilots (GitHub Copilot, Microsoft 365 Copilot) to prevent the submission of proprietary code, PII, or regulated data to external models.
AI Model Registry and Lifecycle Governance
Engineering of a secure, centralized registry to track the lineage, versioning, access, and deployment status of all AI models, ensuring only approved, audited models progress from development to production.
AI-SPM Integration with SIEM/SOAR
Technical integration of AI-SPM tools with existing Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) platforms to unify AI security alerts into enterprise incident response workflows.
Shadow AI Detection in CI/CD Pipelines
Implementation of security gates and code scanning within CI/CD pipelines to detect and block the introduction of unauthorized AI libraries, models, or API dependencies before they reach production environments.
AI-SPM for Regulatory Compliance (GDPR, HIPAA)
Configuration of AI-SPM controls and audit trails specifically to demonstrate compliance with data sovereignty and privacy regulations, mapping AI data flows to articles of GDPR, HIPAA, and other frameworks.
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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.
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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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