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Google Gemini

Rencore monitors Google Gemini across 27 governance policies, 7 reports, and 13 inventories, detecting model access risks, cost overruns, and agent lifecycle issues automatically.

Published For Head of IT, CISO, CIO / CXO
AI & Agents

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Definition

Rencore Gemini governance is a set of 27 policies, 7 reports, 7 segments, and 13 inventories that audit Google's Vertex AI Platform and Agent Builder for security gaps, cost overruns, and operational risks. It detects models deployed without proper access controls, agents with excessive data permissions, and projects exceeding budget thresholds, giving IT visibility into enterprise Google AI usage.

See Google Gemini in Rencore

Step 1 of 4

65 governance capabilities: 13 inventories · 27 policies · 7 reports · 7 segments · 4 automations

Why govern Google Gemini with Rencore

Control model access and permissions

Detect models deployed without proper access controls, projects with overly broad IAM roles, and agents connected to sensitive data sources. Each finding includes severity and recommended remediation.

Track AI spending

Monitor costs across projects, models, and agent invocations. Policies alert when spending exceeds thresholds at the project or organization level. Reports break down costs by model type and team.

Manage agent lifecycle

Identify agents not updated in 90+ days, stale deployments consuming resources, and projects without assigned owners. Reports show agent activity trends and usage patterns.

What Rencore discovers

Rencore automatically inventories these Google Gemini object types.

Gemini Project
Google Cloud project containing Vertex AI and Agent Builder resources
Gemini Model
Custom or tuned ML models registered in Vertex AI Model Registry
Gemini Endpoint
Model serving endpoints that host deployed models for prediction
Gemini Pipeline Job
ML pipeline execution jobs in Vertex AI Pipelines
Gemini Tuning Job
Fine-tuning jobs for foundation models in Vertex AI
Gemini Dataset
Training datasets used for model training and fine-tuning in Vertex AI
Google Gemini inventory card in Rencore

How Gemini governance works in Rencore

Rencore connects to Google’s Vertex AI Platform and Agent Builder via Google Cloud APIs and inventories projects, models, agents, deployments, and data connections. Policies run on every scan cycle and evaluate each resource against governance rules, flagging security, cost, and lifecycle issues.

The multi-vendor AI governance challenge

Organizations using Google Gemini alongside Microsoft 365 Copilot, OpenAI, and Claude need consistent governance across all AI platforms. Rencore provides a unified governance view, detecting the same categories of risk whether your AI workloads run on Google Cloud, Azure, AWS, or third-party platforms.

Who uses Gemini governance

CISOs use it to enforce access controls on model deployments and data connections. Heads of IT track cost trends and identify optimization opportunities. CIOs use adoption reports to compare Google AI usage with other AI platforms across the organization.

Getting started

Provide Rencore with Google Cloud API credentials scoped to Vertex AI. All 27 policies activate on first scan, covering models, agents, projects, and deployments. No per-project configuration required.

Policies

27 governance rules that detect violations and risks.

Google Gemini policies card in Rencore
Gemini notebook runtime in unhealthy state
Detects notebook runtimes that are reporting an unhealthy health state
High Security
Gemini user is an external identity
External (guest) users are a more probable attack vector, raising the likelihood that reachable Vertex AI resources are exploited
Medium Security
Gemini notebook runtime is running
Running notebook runtimes are a live, reachable compute surface, raising the likelihood that any weakness is exploited
Medium Security
Gemini endpoint is serving traffic
Endpoints with deployed models are a live, callable prediction surface, raising the likelihood that any weakness is exploited
Medium Security
Gemini model is deployed and live
Models deployed to endpoints are actively serving predictions, raising the likelihood that any weakness is exploited
Medium Security
Gemini engine is live with data stores
Engines connected to data stores actively serve content to callers, raising the likelihood that any weakness is exploited
Medium Security

Need a rule that isn't listed? Rencore's Policy Builder lets you create custom policies tailored to your organization.

Reports

7 analytics views and dashboards.

Models per Project
Number of custom models in each Google Cloud project
Bar Chart · Adoption
Endpoints per Project
Number of model endpoints in each Google Cloud project
Bar Chart · Adoption
Datasets per Project
Number of datasets in each Google Cloud project
Bar Chart · Adoption
Tuning Jobs by State
Distribution of Vertex AI model tuning jobs by current state
Donut Chart · Operation
Pipeline Jobs by State
Distribution of Vertex AI pipeline jobs by current state
Donut Chart · Operation
Notebook Runtimes by State
Distribution of Vertex AI notebook runtimes by current runtime state
Donut Chart · Operation
Google Gemini reports card in Rencore

Automations

4 automated remediation workflows.

Delete Gemini Agent
Automatically deletes a Gemini agent (Reasoning Engine) after approval
Delete Gemini Endpoint
Automatically deletes a Gemini endpoint after approval
Delete Gemini Data Store
Automatically deletes a Gemini data store after approval
Stop Gemini Notebook Runtime
Automatically stops a Gemini notebook runtime after approval

Segments

7 data groupings for targeted filtering.

Active EndpointsFailed Pipeline JobsSucceeded Pipeline JobsFailed Tuning JobsSucceeded Tuning JobsActive Notebook RuntimesStopped Notebook Runtimes

Frequently asked questions

Does Rencore support governance for AI tools beyond Microsoft Copilot?
Yes. Rencore connects to Claude, OpenAI, Gemini, GitHub Copilot, Cursor, Windsurf, AWS Bedrock, Azure AI Foundry, and other AI platforms. Each connector provides tailored policies for cost management, security, adoption tracking, and access control, giving IT a unified governance view across all AI tools the organization uses.
What is Rencore governance?
Rencore governance is a SaaS platform that continuously monitors your Microsoft 365 tenant for policy violations, configuration drift, and security risks across SharePoint, Teams, Power Platform, Copilot, and AI Agents. It automates compliance evidence collection, surfaces oversharing and sprawl, and provides actionable remediation workflows, reducing manual audit effort by up to 80%.
How do Rencore policies work?
Rencore ships with hundreds of pre-built policies that detect governance violations across every connector, oversharing, sprawl, cost overruns, security risks, and compliance gaps. Policies run on a continuous schedule, evaluate each discovered object against configurable rules, and flag violations with severity (High, Medium, Low), category, and a recommended action.

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