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AI Observability
Do you have full visibility into your data flows, models, AI agents, user activity, and anomalies—across all your AI systems?
AI Security
How confident are you that your current defenses can detect or withstand attacks on your AI systems?
AI Governance
Is your AI and data governance covering access, usage, and compliance robust and up to date across your Data & AI platforms?
The answer to all your concerns is here.
Powerful AI Security, All in One Fabric
Discovery of AI systems
Gain complete visibility across your AI ecosystem.
Automatically detect and catalog AI models, pipelines, APIs, and data flows across platforms like Databricks, Snowflake, Google Vertex AI, and more. Eliminate shadow AI and maintain a real-time inventory to strengthen governance and compliance.
- Discover models, data assets, and pipelines across multi-cloud environments
- Maintain a centralized catalog of models, agents, and data flows
- Track ownership and access: see who owns, builds, or queries each object
- Identify what features models are trained on and how they're being served
Observing AI model behaviors
Monitor how your models behave in the real world.
Gain deep observability into model performance, decisions, and outcomes across diverse inputs and usage scenarios. Detect anomalies, drifts, or misuse and ensure your models behave as intended under all conditions.
- Track model performance across environments, datasets, and user segments
- Detect behavior deviations, including bias, unexpected outputs, and erratic decision paths
- Monitor input and output patterns to spot edge cases or emerging risks
- Compare behavior across versions and environments to detect drift over time
AI threat detection & remediation
Detect, investigate, and respond to AI threats.
Identify and respond to advanced threats like data poisoning, prompt injection, model manipulation, and data leakage. Investigate incidents with full context and launch remediation to contain risks before they impact your AI systems.
- Monitor for sensitive data leakage across model interactions and responses
- Detect advanced AI threats including model inversion, prompt injection, data poisoning, and adversarial inputs
- Investigate incidents with full context, including input/output traces, model decisions, and data lineage
- Automate remediation to isolate compromised components and prevent further impact
Preventive defensive measures
Enforce proactive security with adaptive controls.
Deploy customizable guardrails, usage restrictions, and compliance checks to reduce risk exposure before threats occur. Create secure-by-design AI systems that adapt to changes in behavior, policy, or external risk signals.
- Implement adaptive security policies that evolve based on model behavior and external threats
- Set customizable guardrails and usage restrictions to control how models are used
- Automate compliance and audits to ensure regulatory adherence
- Adjust controls in response to changing risks, behaviors, and governance requirements
AI red teaming & adversarial testing
Simulate real-world attacks to uncover vulnerabilities.
Leverage automated and manual red teaming exercises to stress-test your AI models against sophisticated adversarial tactics. Identify weaknesses in models and agents before they can be exploited. Strengthen your defenses through attack simulations and comprehensive vulnerability assessments.
- Conduct adversarial attacks including prompt injections, data poisoning, and model evasion
- Simulate real-world threats to test AI robustness and response capabilities
- Generate detailed vulnerability reports with actionable remediation guidance
- Integrate red teaming results into security policies
Unified defense across data, models, and agents
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