Best AI Security Software for Azure OpenAI Service

Models can be opaque about what data they failed to perform well on and why. Galileo offers a variety of tools that allow ML teams to quickly inspect and find ML errors up to 10x faster. Galileo automatically analyzes your unlabeled data and identifies data gaps in your model. We get it - ML experimentation can be messy. It requires a lot data and model changes across many runs. You can track and compare your runs from one place. You can also quickly share reports with your entire team. Galileo is designed to integrate with your ML ecosystem. To retrain, send a fixed dataset to the data store, label mislabeled data to your labels, share a collaboration report, and much more, Galileo was designed for ML teams, enabling them to create better quality models faster.

Boost your business with generative AI and avoid the risks. Secure AI use in your organization, from visibility to remediation. Know where your AI is. Get a comprehensive list of all AI-generating apps in your organization. Manage your AI risk. Understand which applications can learn and store your data and what data is associated with each LLM. Aim's continuous business critical insights will give you insights into AI adoption over time. Aim empowers businesses to leverage public generative AI technologies in a secure manner. Discover all shadow AI, expose their risks, and implement real-time policies for data protection. Aim secures your internal LLM deployment. Aim will secure your copilots by eliminating misconfigurations and detecting threats and strengthening trust boundaries.

Acuvity provides the most comprehensive AI governance and security platform for your employees and apps. DevSecOps allows developers to focus on AI Innovation while DevSecOps implements AI Security without code changes. Pluggable AI security ensures complete coverage without outdated libraries or inadequate coverage. By utilizing GPUs only to run LLM models, you can reduce costs. Full visibility of all GenAI models and apps, plugins and services that are being used and explored by your teams. Granular observability of all GenAI interactions, with comprehensive logging. AI usage in enterprises needs a specialized framework that can address new AI risks and comply with emerging AI regulation. Employees can use AI with confidence, without exposing confidential information. Legal wants to make sure that AI-generated content is free of copyright or regulatory issues.