--- title: "Balance AI innovation and governance with Sumo Logic AI and ML apps" page_name: "Balance AI innovation and governance with Sumo Logic AI and ML apps" type: "blog" slug: "sumo-logic-ai-ml-apps-governance" published_at: "2026-06-10" modified_at: "2026-06-10" url: "https://www.sumologic.com/blog/sumo-logic-ai-ml-apps-governance" canonical: "https://www.sumologic.com/blog/sumo-logic-ai-ml-apps-governance" markdown_url: "https://www.sumologic.com/blog/sumo-logic-ai-ml-apps-governance.md" lang: "en" excerpt: "Discover how Sumo Logic’s suite of AI/ML apps—including ChatGPT, Claude, and GitHub Copilot integrations—helps security teams govern LLM usage, monitor spend, and eliminate blind spots." taxonomy_blog_category: - "AI" - "SecOps & Security" --- [ All blogs ](https://www.sumologic.com/blog "blog")[AI](https://www.sumologic.com/blog/ai), [SecOps & Security](https://www.sumologic.com/blog/secops-security) # Balance AI innovation and governance with Sumo Logic AI and ML apps [Margaret Selid](#blog-author-block-361) June 10, 2026 5 min read [AI](https://www.sumologic.com/blog/ai), [SecOps & Security](https://www.sumologic.com/blog/secops-security) ##### Table of contents AI is changing how teams work. Developers are generating code faster, security teams are automating investigations, and employees across the business are using AI tools to accelerate research, content creation, and decision-making. But this adoption comes with a catch. As usage explodes, it introduces a new set of security risks: a rapidly expanding attack surface, faster attack timelines, potential data exposure, and an alarming lack of visibility into how these tools are being used. How do you enable the business to embrace AI without creating massive security blind spots or compromising governance? Following our [recent announcement of the Claude Compliance app](https://www.sumologic.com/blog/sumo-logic-claude-compliance-api-integration), we wanted to highlight some of the apps available in our catalog that can quickly get you the visibility you need. The apps highlighted below give security, compliance, and IT teams the precise visibility and control they need to monitor AI systems, track spend, and detect risky behaviors from a single platform. ## The AI dilemma: Visibility vs. velocity Security teams shouldn’t have to choose between blocking innovation and risking data exposure. When security becomes a bottleneck, users often turn to “[shadow AI](https://www.sumologic.com/blog/rise-shadow-ait),” pasting proprietary code, customer data, or intellectual property into unmanaged tools and creating risks you can’t see. Our AI/ML apps give security and compliance teams the visibility they need to get ahead of that, capturing critical LLM activity, user interaction patterns, and infrastructure performance so you can enable AI adoption without losing sight of what’s happening. Here is a closer look at how these integrations work together across your ecosystem to help you move fast and stay in control. ## LLM compliance ### Anthropic Claude AI compliance Managing user interactions with public and enterprise LLMs is the first line of defense against data leaks. Claude is Anthropic’s enterprise AI assistant, widely adopted for coding, analysis, and content generation across business and technical teams. The Sumo Logic [**Claude Compliance App**](https://www.sumologic.com/help/docs/integrations/saas-cloud/claude-compliance/) brings Claude activity into the centralized platform your enterprise already trusts. By ingesting Claude Enterprise and Claude Platform activity logs, the app provides centralized visibility across API usage, authentication, billing, data access, integrations, SSO, and policy changes, along with prebuilt dashboards and out-of-the-box detections. Every user action is automatically logged with timestamps and IP-level detail, giving compliance teams continuous, searchable audit trails for regulatory peace of mind, and IT teams comprehensive operational visibility—all without adding the overhead of new tools. With this level of visibility, security teams can quickly investigate suspicious access patterns, validate that AI usage aligns with corporate policy, and produce audit-ready reports without hunting across multiple systems. ### OpenAI ChatGPT compliance ChatGPT and Codex are OpenAI’s AI assistants for knowledge work and software development, enabling employees to research, analyze, create content, write code, and automate workflows across the organization. Sumo Logic’s [**ChatGPT Compliance App**](https://www.sumologic.com/help/docs/integrations/saas-cloud/chatgpt-compliance/) delivers deep visibility into how OpenAI’s tools are utilized across your organization. By leveraging detailed metadata, content insights, and rigorous audit trails, this app identifies interaction patterns, flags data-sharing behaviors that violate corporate policy, and surfaces potential compliance risks before they escalate. With this information at their fingertips, compliance and security teams can identify which employees are sharing sensitive data with external AI tools, enforce policy guardrails, and intervene before a potential data exposure becomes a reportable incident. ## Model management As organizations mature, developers often experiment with multiple open-source and proprietary models using proxies like LiteLLM to route requests across providers, which can quickly lead to budget sprawl and fragmented visibility. Sumo Logic’s [**LiteLLM App**](https://www.sumologic.com/help/docs/integrations/saas-cloud/litellm/) brings that activity into view, letting you monitor, manage, and track spend seamlessly across more than 100 different LLMs. With that information in one place, engineering and finance teams can identify cost overruns by team or model, reallocate budget to highest-value use cases, and prevent runaway spend before it becomes a problem. For engineering teams building their own bespoke AI infrastructure, OpenLLMetry is an open-source observability framework that extends OpenTelemetry to capture traces, metrics, and logs from LLM calls, vector databases, and AI agents. The Sumo Logic [**OpenLLMetry App**](https://www.sumologic.com/help/docs/integrations/aiml/opentelemetry/openllmetry/) collects critical LLM, vector database, and AI agent telemetry in standard OTEL formats, so your custom AI applications are just as measurable and secure as your legacy microservices. This telemetry enables engineering teams to pinpoint performance bottlenecks in LLM calls, detect anomalous agent behavior, and maintain the same observability standards they apply to the rest of their infrastructure. ## Developer productivity AI has fundamentally changed software development, but engineering leaders need proof of value alongside security assurances. GitHub Copilot is an AI-powered coding assistant that provides real-time code suggestions, completions, and chat directly within developers’ IDEs. Sumo Logic’s [**GitHub Copilot App**](https://www.sumologic.com/help/docs/integrations/saas-cloud/github-copilot/) delivers actionable visibility into Copilot adoption, engagement, and productivity across your engineering organization. Instead of guessing whether your AI investments are paying off, engineering leaders can track suggestion efficiency, language usage, and chat activity to measure real-world impact. Intuitive dashboards surface adoption trends and flag low-usage or zero-engagement teams, so you can optimize license spend, target enablement where it’s needed, and build a clear business case for your AI tooling investments. ## Enterprise cloud AI monitoring Organizations leveraging heavy-duty cloud AI infrastructure must keep a close eye on the underlying platform runtime. ### AWS AI monitoring Amazon Bedrock is AWS’s fully managed service for accessing and deploying foundation models from leading AI providers, including building and running autonomous AI agents. The Sumo Logic [**Amazon Bedrock**](https://www.sumologic.com/help/docs/integrations/amazon-aws/amazon-bedrock/) and [**Bedrock AgentCore Apps**](https://www.sumologic.com/help/docs/integrations/amazon-aws/amazon-bedrock-agentcore/) offer deep insights into CloudTrail, CloudWatch Logs, and runtime performance metrics. These preconfigured dashboards allow you to monitor logs and track the health of Bedrock services, including agent runtimes, memory allocations, API gateways, built-in tools, and identity services. That operational data enables cloud and security teams to detect misconfigured agents, respond to runtime anomalies, and ensure their AI infrastructure meets the same compliance bar as the rest of their AWS environment. For teams building custom models, Amazon SageMaker is AWS’s end-to-end platform for building, training, and deploying custom machine learning models at scale. Keep a close eye on your custom machine learning pipelines by monitoring the logs and performance metrics of your training and deployment builds with the Sumo Logic [**Amazon SageMaker App**](https://www.sumologic.com/help/docs/integrations/amazon-aws/amazon-sagemaker/). With that visibility, ML engineers can catch failed training runs early, track model performance over time, and ensure deployments are behaving as expected in production. ### Microsoft AI monitoring Microsoft shops turn to Azure Machine Learning, their cloud platform for building, training, and operationalizing ML models across distributed compute resources. Track training runs, model deployments, and resource utilization across the individual nodes in your workspace with the Sumo Logic [**Azure Machine Learning App**](https://www.sumologic.com/help/docs/integrations/microsoft-azure/azure-machine-learning/). Platform and ML ops teams can identify idle compute resources, troubleshoot deployment failures, and optimize costs across distributed workloads. Microsoft Foundry is Microsoft’s enterprise platform for customizing, fine-tuning, and deploying AI models on top of proprietary data and infrastructure. Sumo Logic’s [**Microsoft Foundry App**](https://www.sumologic.com/help/docs/integrations/microsoft-azure/microsoft-foundry/) provides critical operational clarity into the activities, health, and status of your Microsoft Foundry resources, ensuring your enterprise data fabrics are running optimally and securely. With that additional clarity, IT and security teams can monitor for unauthorized access to proprietary data, validate that fine-tuned models are performing within expected parameters, and maintain governance over AI built on top of their most sensitive assets. ## Get started AI adoption shouldn’t create new organizational silos or operational blind spots. By integrating these AI and ML apps with Sumo Logic, your organization gains the confidence to innovate rapidly while maintaining a rigorous, centralized security posture. Give your business units the freedom to use cutting-edge AI tools, confident that your security team has the full context, visibility, and control to protect corporate assets. Ready to secure your AI pipeline and optimize your deployment? Head over to the [**Sumo Logic App Catalog**](https://www.sumologic.com/app-catalog) to explore the AI/ML category to get started. Or [request a personalized demo](https://www.sumologic.com/request-demo) with our team today. We add new apps and integrations every month, so keep an eye on the AI/ML section of the App Catalog for the latest selection. ### Article Tags - [AI](https://www.sumologic.com/blog/ai) - [SecOps & Security](https://www.sumologic.com/blog/secops-security) Margaret Selid Principal Product Marketing Manager Margaret is an experienced product marketing leader with a passion for distilling complex technology and ideas into compelling stories. Before joining Sumo Logic, she worked in supply chain technology launching visibility products, after several years promoting cities for economic investment. 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