Holistic AI

Categories: Automation / Agents, Business & Sales, Cybersecurity | Pricing: Enterprise | Official Website ↗

Holistic AI provides an end-to-end AI governance platform for enterprises to identify, protect, and enforce compliance for their AI systems.

Holistic AI is an enterprise AI governance platform designed to help organizations manage and mitigate risks associated with AI adoption. It addresses challenges like shadow AI, unmanaged risks, and manual compliance processes by offering automated solutions for discovery, risk assessment, and regulatory enforcement. The platform aims to accelerate AI deployment by turning governance into an infrastructure rather than a bottleneck. The platform offers three core functions: Identify, Protect, and Enforce. It automatically scans cloud platforms, code repositories, and SaaS applications to build a comprehensive AI inventory, detecting models, agents, APIs, and workflows across various integrations. For protection, it runs over 40 specialized tests for bias, safety, security, and performance, including AI red teaming and monitoring for drift and degradation. For enforcement, it automates compliance workflows, collects audit evidence, and applies policies using built-in frameworks like EU AI Act, NIST AI RMF, and ISO 42001.

Key Features

AI Discovery and Inventory
Continuous AI Risk Assessment and Monitoring
Automated Compliance Workflows
AI Red Teaming and LLM Testing
Bias and Fairness Auditing
Guardian Agents for real-time AI oversight
Built-in regulatory frameworks (EU AI Act, NIST AI RMF, ISO 42001)
Continuous audit trails and evidence collection

Pros

Automatically identifies and inventories all AI systems, including shadow AI.
Continuously assesses and monitors AI for bias, security, and performance risks.
Automates compliance workflows and generates audit-ready evidence.
Provides real-time oversight for autonomous AI agents with Guardian Agents.
Integrates with major cloud platforms and code repositories.

Cons

Pricing information is not transparently available.
Requires enterprise-level implementation and integration.
Focuses on governance, not direct AI development or deployment.
May have a learning curve for complex regulatory frameworks.
Specific details on supported integrations beyond 20+ are not listed.

Use Cases

Identifying and eliminating shadow AI across an organization
Protecting AI models and applications against risk and bias
Enforcing regulatory compliance for AI systems
Automating AI risk management and monitoring
Ensuring responsible AI adoption and scaling

Best For

Global enterprises running AI at scale
Organizations needing to comply with AI regulations (EU AI Act, NIST AI RMF)
Companies struggling with shadow AI and ungoverned AI systems
Security, Legal, and Board teams requiring AI assurance

Integrations: AWS, Azure, GitHub, Databricks, 20+ other integrations

Platforms: Web

Watch demo on YouTube ↗

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