Skip to main content

Getting Started with Infotechtion AI Governance

Welcome to Infotechtion's AI Governance platform. This guide will walk you through the step-by-step process to enable AI governance capabilities in your organization, starting with the AI Governance Databot — your central hub for detecting AI usage, identifying sensitive data at risk, and managing compliance.

Overview: Your AI Governance Journey​

The Infotechtion AI Governance platform enables you to:

  1. Discover all AI agents and tools in use across your organization
  2. Identify sensitive data being accessed or transferred to AI systems
  3. Analyze risks associated with AI usage patterns
  4. Report on compliance status and governance posture
  5. Control AI behavior through policies (roadmap: Agentic Operations)

The entire process is managed through the AI Governance Databot — a unified interface where authorized auditors and governance teams interact with findings and manage AI governance policies.

Prerequisites​

Before getting started, ensure you have:

  • Organization Admin Access or delegated governance permissions
  • Access to your Microsoft 365, Azure, or AWS environments (depending on where AI agents are deployed)
  • Telemetry and Audit Log permissions in your tenant
  • A designated AI Governance team or stakeholder group

Step 1: Connect Your Data Sources​

The first step to AI governance is ensuring the platform can see your data landscape. This requires connecting your organization's data repositories and telemetry sources to the Infotechtion SaaS platform.

1.1 Access Platform Configuration​

  1. Log into the Infotechtion AI Governance Portal
  2. Navigate to Settings → Data Sources
  3. Click + Add Data Source

1.2 Select Your Environment​

Choose the platforms where AI agents may be operating:

  • Microsoft 365 (Microsoft Teams, OneDrive, SharePoint, Exchange)
  • Azure AI Foundry (Azure OpenAI, Copilot, Custom Models)
  • AWS (Bedrock, SageMaker, Custom LLMs)
  • Third-Party AI Tools (ChatGPT, Claude, Custom Integrations)
  • On-Premises Systems (if applicable)

1.3 Authorize Platform Access​

For each data source, authorize Infotechtion to:

  • Scan and Index: Discover all AI agents and LLMs in use
  • Collect Telemetry: Gather logs of AI interactions and data access patterns
  • Classify Data: Identify and label sensitive data (PII, PHI, Trade Secrets)
  • Monitor Audit Trails: Track all activities related to AI usage

Authorization Method:

  • Use OAuth 2.0 or Service Principal authentication
  • Assign minimal required permissions (principle of least privilege)
  • Review and approve requested scopes

1.4 Verify Connection Status​

Once authorized:

  1. Click Test Connection to verify authentication
  2. Wait for initial data ingestion (typically 15-30 minutes for first scan)
  3. Confirm Status: Connected appears in green

Step 2: Enable Telemetry Collection​

Telemetry collection allows Infotechtion to understand how AI is being used in your organization and what data it accesses.

2.1 Configure Telemetry Settings​

Navigate to Settings → Telemetry & Monitoring

Enable the following collection modes:

Telemetry TypePurposeStatus
AI Agent InteractionsTrack every use of AI agents and LLMsEnable
Data Access LogsMonitor what data AI systems accessEnable
User Behavior TrackingRecord who uses AI and whenEnable
Data Transfer MonitoringCapture data sent to AI systemsEnable
Sensitive Data EventsAlert on PII/PHI exposure to AIEnable
Anomaly Detection SignalsReal-time behavioral analysisEnable

2.2 Set Data Retention Policy​

Define how long telemetry data is retained:

  • Minimum Retention: 90 days (for incident investigation)
  • Recommended Retention: 12 months (for compliance audits)
  • Extended Retention: Custom based on regulatory requirements

2.3 Configure Privacy Controls​

  • Data Anonymization: Mask personally identifiable information where appropriate
  • Sampling Rates: For high-volume environments, configure sampling if needed
  • Exclusion Rules: Exclude non-sensitive data categories to optimize performance

Step 3: Deploy the AI Classification Engine​

The AI Classification Engine automatically identifies and categorizes your organization's data, enabling risk-aware governance.

3.1 Enable Data Classification​

Navigate to Settings → Data Classification

  1. Select Microsoft Classifiers or Custom Classifiers
  2. Define sensitive data categories:
    • PII (Personal Identifiable Information)
    • PHI (Protected Health Information)
    • Trade Secrets & Intellectual Property
    • Financial Data
    • Other Custom Classifications

3.2 Set Classification Rules​

  • Automatic Labeling: Enable automatic detection and labeling of sensitive content
  • Quarantine Rules: Define actions when sensitive data is detected near AI systems
  • Alert Thresholds: Set sensitivity levels for notifications

3.3 Validate Classification​

Review the classification results in your first scan:

  1. Go to Discovery → Data Inventory
  2. Verify accuracy of classified data
  3. Refine rules if needed

Step 4: Initialize AI Agent Discovery​

Now that data sources are connected and telemetry is enabled, begin discovering all AI agents in your environment.

4.1 Start Discovery Scan​

Navigate to Governance Databot → Discovery

  1. Click Start Discovery Scan

  2. Select scope:

    • Full Organization
    • Specific Departments/Divisions
    • Specific Teams/Business Units

  3. Click Run Scan (First scan may take 30 minutes to several hours depending on environment size)

4.2 Review Discovery Results​

Once the scan completes, you'll see:

  • Total AI Agents Discovered: All agents across your environment
  • Sanctioned vs. Shadow AI: Breakdown of authorized vs. unauthorized tools
  • Agent Categories:
    • Copilot & Microsoft AI
    • Third-Party Plugins
    • Custom AI Applications
    • Unknown/Shadow AI Tools

4.3 Classify Agents​

For each discovered agent, the platform automatically creates an Agent Card that includes:

  • Agent Name & Type: Identifies the specific AI tool
  • Data Access Level: What data the agent can access
  • Risk Classification: EU AI Act risk tier (Unacceptable, High, Limited, Minimal)
  • Autonomy Level: Can the agent act without human approval?
  • Authority Limits: What can the agent do?

Review and validate each Agent Card for accuracy.

Step 5: Access the AI Governance Databot​

The Governance Databot is your unified control center for managing AI governance. It's where authorized users interact with all platform findings and capabilities.

5.1 Databot Overview​

The Databot provides three core modes of operation:

Mode 1: Discovery​

  • View all discovered AI agents in your environment
  • See Shadow AI and unauthorized tools
  • Understand data lineage and agent connections
  • Monitor which teams are using which AI systems

Mode 2: Analysis​

  • Analyze AI usage patterns and trends
  • Identify behavioral anomalies
  • Detect suspicious or risky AI activities
  • Understand data flows to/from AI systems
  • Risk scoring for each agent

Mode 3: Reporting​

  • Generate compliance reports (EU AI Act, UK AI White Paper, ISO 42001)
  • Create audit-ready documentation
  • Track Agent Card changes and audit history
  • Export findings for stakeholder review
  • Dashboard visualizations of governance posture

5.2 Access the Databot​

  1. Log into the Infotechtion Portal
  2. Click Governance Databot
  3. You'll be presented with a role-restricted interface based on your permissions:
    • Governance Admins: Full access to all features
    • Auditors: View-only access to analysis and reports
    • Data Stewards: View data classifications and access logs

Step 6: Understand Your Initial Findings​

6.1 Review Discovery Dashboard​

The Discovery dashboard shows:

  • Total Agents: Count of all AI systems discovered
  • Shadow AI Detected: Unvetted tools bypassing controls
  • Data at Risk: Sensitive information accessible to AI
  • Compliance Status: Your current governance readiness

6.2 Analyze Sensitive Data Exposure​

In the Analysis section, you'll see:

  • Which AI systems access sensitive data: PII, PHI, Trade Secrets
  • Data Transfer Events: When data was sent to AI systems
  • Risk Indicators: Behavioral flags suggesting potential misuse
  • User Patterns: Who is using AI and how frequently

6.3 Identify Risky Agents​

The platform automatically flags agents with:

  • Unauthorized Data Access: Accessing data beyond defined scope
  • Anomalous Behavior: Usage patterns that deviate from baseline
  • High Risk Classification: Agents processing sensitive data
  • Compliance Violations: Agents not meeting regulatory requirements

6.4 Generate Initial Reports​

Create your first compliance report:

  1. Navigate to Reporting → Create Report
  2. Select report type:
    • Executive Summary
    • Detailed Compliance Analysis
    • Agent Risk Assessment
    • Data Flow Documentation
  3. Choose regulatory framework (EU AI Act, UK AI White Paper, etc.)
  4. Click Generate Report

Step 7: Configure Governance Policies​

With visibility into your AI landscape, establish governance policies to control AI behavior.

7.1 Define Agent Policies​

Set policies for each agent or agent category:

  • Data Access Restrictions: Which data sources can the agent access?
  • User Approval Requirements: Does the agent require human approval before acting?
  • Output Restrictions: What can the agent output or send?
  • Time Restrictions: When can the agent operate?
  • Volume Limits: How much data can it process?

7.2 Set Alerts & Escalations​

Configure alerts for:

  • Shadow AI Detection: Alert when new unauthorized tools are discovered
  • Sensitive Data Access: Alert when AI accesses classified information
  • Policy Violations: Alert when agents exceed defined bounds
  • Behavioral Anomalies: Alert on unusual access patterns
  • Compliance Breaches: Immediate alert on regulatory violations

7.3 Define Remediation Actions​

Specify automatic and manual responses:

  • Automatic Actions: Quarantine data, disable agent access, create tickets
  • Manual Actions: Require security team approval before taking action
  • Escalation Path: Define who gets notified and in what order

Step 8: Monitor & Respond​

8.1 Continuous Monitoring​

The Databot continuously monitors:

  • AI Agent Usage: Real-time tracking of all AI interactions
  • Data Flows: Monitoring what data is accessed and transferred
  • Policy Compliance: Ensuring agents stay within defined bounds
  • Risk Events: Detecting suspicious or risky behavior

8.2 Investigate Findings​

When the Databot flags a finding:

  1. Review the alert in Alerts dashboard
  2. Click to open the Incident Details
  3. Analyze the evidence:
    • What data was involved?
    • Which users/agents were involved?
    • What actions were taken?
    • What's the risk level?

8.3 Take Action​

Respond to findings:

  • Approve: If behavior is legitimate, approve and add to whitelist
  • Investigate: Open a formal investigation workflow
  • Remediate: Take corrective action (disable agent, restrict access, etc.)
  • Document: Record all findings for audit trail

Step 9: Reporting & Compliance​

9.1 Regular Reporting​

Establish a regular reporting cadence:

  • Weekly: Operational metrics (AI usage, new agents discovered)
  • Monthly: Compliance status and trend analysis
  • Quarterly: Executive summaries and governance posture
  • Annual: Comprehensive compliance audit documentation

9.2 Audit-Ready Documentation​

The platform maintains comprehensive documentation:

  • Agent Inventory: All discovered agents and their properties
  • Data Lineage: Complete tracking from data source to AI system
  • Access Logs: Who accessed what, when, and why
  • Policy Changes: Audit trail of all governance modifications
  • Incident Records: Documentation of all security events and responses

9.3 Regulatory Compliance​

Generate compliance reports for:

  • EU AI Act: Risk classification, transparency obligations, high-risk AI monitoring
  • UK AI White Paper: Five-principle alignment (Safety, Transparency, Fairness, Accountability, Contestability)
  • GDPR: Data protection impact assessments, data subject rights
  • ISO 42001: AI Management System standards
  • Industry-Specific Regulations: HIPAA, SOX, etc.

Step 10: Roadmap - Agentic Operations (Future Capability)​

The Infotechtion AI Governance platform roadmap includes Agentic Operations, which will extend current capabilities with automated control and orchestration.

10.1 What are Agentic Operations?​

Agentic Operations enable the Governance Databot to:

  • Automatically enforce policies: Instead of just detecting violations, automatically take corrective actions
  • Self-remediate issues: Quarantine problematic agents, revoke data access, pause operations
  • Orchestrate responses: Coordinate multi-step remediation workflows
  • Learn and adapt: Improve policies based on outcomes
  • Provide recommendations: AI-driven suggestions for policy optimization

10.2 Expected Capabilities​

  • Autonomous Policy Enforcement: Automatic blocking of policy violations without human intervention
  • Intelligent Escalation: Smart routing of issues to appropriate teams based on severity
  • Threat Response Automation: Automatic response to detected threats or misuse
  • Continuous Compliance: Automated adjustments to maintain regulatory compliance
  • Self-Tuning Controls: Learning-based optimization of governance rules

10.3 Staying Informed​

Watch for updates on Agentic Operations:

  • Check the Roadmap 2025 for timeline and details
  • Subscribe to product updates at www.infotechtion.com
  • Contact your account manager for early access to beta features

Next Steps​

  1. Start Now: Follow Steps 1-5 to get your platform connected and running
  2. Review Findings: Complete Steps 6-8 to understand your current AI governance posture
  3. Establish Governance: Implement policies in Step 7 tailored to your organization
  4. Monitor Continuously: Use Step 8-9 for ongoing compliance and reporting
  5. Plan for the Future: Prepare for Agentic Operations capabilities in Step 10

Support & Resources​

Summary​

By following this guide, you've established a foundation for comprehensive AI governance:

  • Visibility: You can now see all AI agents and their data access
  • Understanding: You understand which data is at risk and how AI uses it
  • Control: You have policies in place to manage AI behavior
  • Compliance: You're prepared to demonstrate compliance to regulators
  • Future-Ready: You're positioned to adopt Agentic Operations for automated governance

Welcome to responsible AI governance with Infotechtion!