# Areebi

> The secure control plane for enterprise AI. Deploy privately, control access, protect data, and stay compliant.

Areebi is an AI governance platform that provides enterprise-grade security, data loss prevention, policy enforcement, audit logging, and compliance automation for organizations using AI.

## Core Capabilities
- Real-time DLP and PII masking across all AI interactions
- Visual policy builder with no-code rule engine
- Immutable audit logging for compliance evidence
- Shadow AI detection and prevention
- Support for 30+ LLM providers (model-agnostic)
- Private deployment: Docker, Kubernetes, on-premises, private cloud
- Compliance templates for 20+ frameworks including HIPAA, SOC 2, GDPR, EU AI Act, Australian Privacy Act

## Key Definitions
- What is AI Governance?: AI governance is the framework of policies, processes, and controls that organizations use to ensure artificial intelligence is deployed responsibly, securely, and in compliance with regulations.
- What is Shadow AI?: Shadow AI refers to the use of artificial intelligence tools and services by employees without the knowledge, approval, or oversight of an organization's IT or security teams.
- What is AI DLP?: AI DLP (Data Loss Prevention for AI) is a security control that monitors, detects, and prevents sensitive data - including PII, PHI, financial data, and intellectual property - from being exposed through AI tools and large language model interactions.
- What is Prompt Injection?: Prompt injection is a security attack where malicious instructions are embedded in user inputs to manipulate a large language model into ignoring its original instructions, bypassing safety controls, or producing unauthorized outputs.
- What is an AI Firewall?: An AI firewall is a security layer that sits between users and AI models, inspecting and filtering prompts and responses in real-time to enforce security policies, prevent data leakage, and block prompt injection attacks.
- What is AI Compliance?: AI compliance is the practice of ensuring that artificial intelligence systems meet the legal, regulatory, and ethical requirements set by applicable laws and industry standards across all jurisdictions where an organization operates.
- What is Algorithmic Discrimination?: Algorithmic discrimination occurs when an AI system produces outputs that unfairly disadvantage individuals or groups based on protected characteristics such as race, gender, age, or disability, often due to biased training data or flawed model design.
- What is AI Risk Management?: AI risk management is the systematic process of identifying, assessing, mitigating, and monitoring risks associated with the development, deployment, and use of artificial intelligence systems throughout their lifecycle.
- What is AI Transparency?: AI transparency is the principle that organizations deploying AI systems must be open about how those systems work, what data they use, how decisions are made, and when users are interacting with AI rather than a human.
- What is Automated Decision-Making?: Automated decision-making (ADM) is the process of making decisions about individuals using algorithms or AI systems with limited or no human involvement, particularly decisions that significantly affect rights, opportunities, or access to services.
- What is an AI Audit?: An AI audit is a structured evaluation of an AI system's compliance with regulatory requirements, organizational policies, ethical standards, and technical performance benchmarks, typically conducted by independent assessors.
- What is Responsible AI?: Responsible AI is an approach to developing, deploying, and operating artificial intelligence systems that prioritizes fairness, transparency, accountability, privacy, safety, and human oversight throughout the AI lifecycle.
- What is AI Bias Testing?: AI bias testing is the process of systematically evaluating AI systems for discriminatory patterns in their outputs, using statistical methods to detect disparate impact across protected groups before and after deployment.
- What is AI Observability?: AI observability is the practice of gaining comprehensive visibility into how AI systems are being used across an organization, what data flows through them, and whether they are performing as expected - enabling governance, cost control, and risk management at scale.
- What is AI Compliance Automation?: AI compliance automation is the use of technology to continuously and automatically enforce, monitor, and evidence an organization's adherence to AI-related laws, regulations, and standards, replacing manual checklists and periodic audits with real-time, machine-driven compliance controls.
- What is an AI Policy Engine?: An AI policy engine is an automated system that defines, enforces, and monitors organizational rules governing how AI tools are used, what data can be processed, which models are accessible, and what outputs are permitted - replacing manual policy enforcement with real-time, programmatic controls.
- What is an AI Control Plane?: An AI control plane is the centralized management layer that governs policies, access, data protection, compliance, and observability across all AI usage in an organization - separating the management of AI from the execution of AI interactions.
- What is Adversarial Robustness?: Adversarial robustness is the ability of an AI system to maintain correct, safe, and predictable behavior when subjected to deliberately crafted adversarial inputs designed to cause misclassification, policy bypass, data leakage, or other unintended outcomes.
- What is Model Drift?: Model drift is the degradation of an AI model's performance over time as the statistical properties of real-world data diverge from the data the model was trained on, causing predictions and outputs to become less accurate, less relevant, or potentially unsafe.
- What is Data Poisoning?: Data poisoning is an adversarial attack in which an attacker deliberately corrupts the training, fine-tuning, or retrieval data used by an AI system, embedding malicious patterns that cause the model to produce incorrect, biased, or harmful outputs when triggered by specific inputs.
- What is Differential Privacy?: Differential privacy is a mathematical framework that provides provable guarantees about the privacy of individuals in a dataset by adding carefully calibrated noise to data queries, model training, or outputs - ensuring that no single individual's data can be identified or reconstructed from the results.
- What is AI Red Teaming?: AI red teaming is the practice of systematically probing AI systems through adversarial testing - simulating real-world attacks, misuse scenarios, and edge cases - to identify vulnerabilities, safety failures, and governance gaps before they can be exploited in production.
- What are Model Cards?: Model cards are standardized documentation artifacts that describe an AI model's intended use, performance characteristics, training data, limitations, ethical considerations, and evaluation results - providing transparency and accountability for anyone who develops, deploys, or is affected by the model.
- What is Federated Learning Security?: Federated learning security encompasses the techniques, protocols, and governance practices that protect distributed machine learning systems - where models are trained across multiple decentralized devices or organizations without centralizing raw data - from adversarial attacks, privacy leakage, model poisoning, and inference threats.
- What is AI Supply Chain Security?: AI supply chain security is the practice of identifying, assessing, and mitigating risks across the entire chain of third-party dependencies that enterprise AI systems rely on - including pre-trained models, training datasets, open-source libraries, model hosting providers, data annotation services, and plugin ecosystems.
- What is AI Incident Response?: AI incident response is the structured process organizations use to detect, triage, contain, eradicate, recover from, and learn from incidents involving AI systems - including prompt injection attacks, data leakage through prompts, model behavior failures, data poisoning, and emergent harmful outputs from generative models.
- What is AI Vendor Risk?: AI vendor risk is the set of confidentiality, integrity, availability, compliance, and operational risks an organization inherits when it relies on third-party AI providers, sub-processors, and model-as-a-service supply chains - including foundation model vendors, fine-tuning data providers, hosted inference platforms, AI plugin marketplaces, and downstream SaaS products that embed third-party AI.
- What is Data Residency for AI?: Data residency for AI is the discipline of controlling where AI prompts, responses, embeddings, fine-tuning corpora, and training data are stored and processed.
- What is AI Runtime Policy?: AI runtime policy is the set of identity-aware, content-aware, and context-aware rules enforced at the prompt and response boundary of an AI system - in real time, on every interaction.
- What is Prompt Engineering Security?: Prompt engineering security is the discipline of designing prompts, prompt templates, and the surrounding system architecture so that the resulting AI behaviour is resistant to prompt injection, jailbreak, role confusion, instruction override, and unintended tool invocation.
- What is AI Rate Limiting?: AI rate limiting is the discipline of controlling the rate, volume, and cost of requests against AI systems - across users, tenants, agents, and downstream services - to prevent abuse, denial of service, data-exfiltration via excessive querying, runaway model spend, and breach of regulatory or contractual usage limits.
- What is Agent Governance?: Agent governance is the discipline of governing autonomous AI agents - systems that take multi-step actions on behalf of users or organisations - across their full lifecycle.
- What is AI Attribution?: AI attribution is the practice of tracing AI-system outputs back to their inputs, prompts, retrieved sources, training data lineage, and the user or tenant context that produced them.
- What is Retrieval-Augmented Generation (RAG)?: Retrieval-Augmented Generation (RAG) is an AI architecture that combines a large language model with an external knowledge source - usually a vector database of an organization's own documents - so that the model retrieves relevant context at query time and grounds its generated responses in that retrieved evidence rather than relying solely on parametric memory from training.
- What is LLM Fine-Tuning?: LLM fine-tuning is the process of continuing the training of a pretrained large language model on a smaller, task-specific or domain-specific dataset so that the model's weights shift to better reflect the desired behavior, style, or knowledge - producing a derived model that retains the base model's general capabilities while specializing in the customer's task.
- What is Agentic AI?: Agentic AI is the class of AI systems that go beyond responding to a single prompt - they plan multi-step actions, call external tools, write to systems of record, and pursue a goal across multiple turns - making their behavior more powerful than a chat model but also far harder to govern, because the system is taking actions in the world rather than merely producing text.
- What is a Private LLM?: A private LLM is a large language model deployed so that prompts, responses, and any documents it processes remain inside infrastructure the organisation controls - on-premise servers, a private cloud tenancy, an air-gapped environment, or a local machine - rather than being sent to a shared public AI service.
- What is an LLM Gateway?: An LLM gateway is a single API endpoint that sits between your applications and one or more large language model providers, centralising routing, authentication, rate limiting, cost tracking, caching, data loss prevention, and audit logging so that every AI request passes through one governed control point rather than each application calling each model directly.
- What is LLM Security?: LLM security is the discipline of protecting large language model applications across their full lifecycle - the prompts and data flowing in, the model and its supply chain, the runtime that serves it, and the outputs and actions it produces - against threats such as prompt injection, sensitive-data disclosure, insecure output handling, and supply-chain compromise, using a combination of inline runtime controls, governance, and monitoring.
- What is RAG Security?: RAG security is the practice of protecting retrieval-augmented generation systems against the risks unique to coupling a large language model with an external knowledge base - poisoned or malicious documents, access-control bypass where the retriever surfaces data a user is not entitled to, embedding inversion and leakage, and indirect prompt injection through retrieved content - by enforcing access control at retrieval time, sanitising ingested and retrieved content, and treating the vector store as a regulated data asset.
- What is AI TRiSM?: AI TRiSM (AI Trust, Risk and Security Management) is a framework defined by Gartner for governing artificial intelligence across four pillars - explainability and model monitoring, AI application security, data and content anomaly detection, and AI governance - so that organisations can ensure their AI models and applications are trustworthy, fair, reliable, robust, and protect data privacy.
- What is an Enterprise LLM?: An enterprise LLM is a large language model deployment that adds the controls an organisation requires to use AI at scale safely - single sign-on and role-based access control, immutable audit logging, real-time data loss prevention, data residency control, and a policy engine - on top of the raw model, so that the deployment is governed, attributable, compliant, and integrated with enterprise identity rather than being a bare model endpoint.

## Documentation

### Platform
- [Platform Overview](https://www.areebi.com/platform)
- [AI Control Plane](https://www.areebi.com/ai-control-plane)
- [Product Tour](https://www.areebi.com/product-tour)
- [Pricing](https://www.areebi.com/pricing)

### Compliance
- [NIST AI Risk Management Framework (AI RMF 1.0) Compliance](https://www.areebi.com/compliance/nist-ai-rmf)
- [ISO/IEC 42001 AI Management Systems Compliance](https://www.areebi.com/compliance/iso-42001)
- [UK AI Governance & Regulation Compliance Guide](https://www.areebi.com/compliance/uk-ai-governance)
- [Colorado AI Act (SB 24-205) Compliance Guide](https://www.areebi.com/compliance/colorado-ai-act)
- [California AI Transparency Act (SB 942) Compliance Guide](https://www.areebi.com/compliance/california-ai-transparency)
- [Australia AI Governance & Privacy Act Compliance Guide](https://www.areebi.com/compliance/australia-ai-governance)
- [Canada AI Governance & Post-AIDA Compliance Guide](https://www.areebi.com/compliance/canada-ai-governance)
- [Singapore Model AI Governance Framework Compliance Guide](https://www.areebi.com/compliance/singapore-ai-governance)
- [NYC Local Law 144 - AI Hiring Bias Audit Compliance](https://www.areebi.com/compliance/nyc-local-law-144)
- [PCI-DSS 4.0 Compliance for AI Systems](https://www.areebi.com/compliance/pci-dss-4)
- [FedRAMP for AI Platforms - Authorization Guide](https://www.areebi.com/compliance/fedramp-ai)
- [New Zealand AI Governance & Compliance Guide](https://www.areebi.com/compliance/new-zealand-ai-governance)
- [OECD AI Principles - International AI Governance Framework](https://www.areebi.com/compliance/oecd-ai-principles)
- [Illinois AI Video Interview Act Compliance Guide](https://www.areebi.com/compliance/illinois-ai-video-interview)
- [FTC AI Enforcement Actions & Compliance Guide](https://www.areebi.com/compliance/ftc-ai-enforcement)
- [SEC AI Disclosure Guidance & Compliance](https://www.areebi.com/compliance/sec-ai-disclosure)
- [UK Online Safety Act & AI Compliance Guide](https://www.areebi.com/compliance/uk-online-safety-act)
- [CCPA and AI: California Consumer Privacy Act Compliance](https://www.areebi.com/compliance/ccpa)
- [FERPA and AI: Educational Data Privacy Compliance](https://www.areebi.com/compliance/ferpa)
- [SOX and AI: Sarbanes-Oxley Compliance for AI-Driven Financial Reporting](https://www.areebi.com/compliance/sox-ai)
- [GLBA and AI: Gramm-Leach-Bliley Act Compliance for AI Systems](https://www.areebi.com/compliance/glba)
- [Texas AI Laws: TRAIGA (HB 149) and HB 2060 Compliance Guide](https://www.areebi.com/compliance/texas-ai-laws)
- [Japan AI Guidelines for Business: METI/MIC, Hiroshima Process, and the AI Promotion Act](https://www.areebi.com/compliance/japan-ai-guidelines)
- [South Korea AI Basic Act (AI Framework Act): 2026 Compliance Guide](https://www.areebi.com/compliance/south-korea-ai-act)
- [India AI Regulation: DPDPA 2023 and the Proposed Digital India Act](https://www.areebi.com/compliance/india-digital-india-act-ai)
- [Brazil AI Regulation: LGPD and the Proposed Marco Legal da IA (PL 2338/2023)](https://www.areebi.com/compliance/brazil-lgpd-ai)
- [UAE AI Compliance: PDPL (Federal Decree-Law 45/2021) + DIFC + ADGM data laws](https://www.areebi.com/compliance/uae-pdpl)
- [NIS2 Directive + AI: cybersecurity obligations for AI-enabled essential entities (EU 2022/2555)](https://www.areebi.com/compliance/nis2-directive-ai)
- [APRA CPS 230 and AI: Operational Risk for Australian Financial Services](https://www.areebi.com/compliance/apra-cps-230-ai)
- [APRA CPS 234 & AI: Securing AI Models, Pipelines and Inference APIs](https://www.areebi.com/compliance/apra-cps-234-ai)
- [Privacy Act Automated Decision-Making (ADM) Transparency: The 10 December 2026 Deadline](https://www.areebi.com/compliance/privacy-act-adm-transparency)
- [Australia's AI Rules in 2026: No AI Act, the National AI Plan and the 6 Essential Practices](https://www.areebi.com/compliance/australian-voluntary-ai-safety-standard)
- [Sovereign and Self-Hosted AI in Australia: Data Residency, Sovereignty and Compliance](https://www.areebi.com/compliance/sovereign-ai-australia)
- [DTA Policy for the Responsible Use of AI in Government: 2026 Mandatory Requirements](https://www.areebi.com/compliance/dta-ai-policy)
- [ASD Essential Eight and AI: Securing AI Systems to the Australian Cyber Baseline](https://www.areebi.com/compliance/essential-eight-ai)
- [IRAP, the ISM and PSPF for AI: Running AI Workloads in Australian Government Environments](https://www.areebi.com/compliance/irap-ism-ai)
- [ASIC REP 798 and Directors' AI Duties: Closing the Financial Services Governance Gap](https://www.areebi.com/compliance/asic-rep-798-ai)
- [The SOCI Act and AI: Critical Infrastructure Risk Management for AI Systems and Data Stores](https://www.areebi.com/compliance/soci-act-ai)

### Compliance by Industry
- [HIPAA Compliance for Healthcare AI](https://www.areebi.com/compliance/hipaa/healthcare-ai)
- [HIPAA Compliance for Financial Services AI](https://www.areebi.com/compliance/hipaa/financial-services-ai)
- [HIPAA Compliance for Legal AI](https://www.areebi.com/compliance/hipaa/legal-ai)
- [HIPAA Compliance for Government AI](https://www.areebi.com/compliance/hipaa/government-ai)
- [SOC 2 Compliance for Healthcare AI](https://www.areebi.com/compliance/soc-2/healthcare-ai)
- [SOC 2 Compliance for Financial Services AI](https://www.areebi.com/compliance/soc-2/financial-services-ai)
- [SOC 2 Compliance for Legal AI](https://www.areebi.com/compliance/soc-2/legal-ai)
- [SOC 2 Compliance for Government AI](https://www.areebi.com/compliance/soc-2/government-ai)
- [GDPR Compliance for Healthcare AI](https://www.areebi.com/compliance/gdpr/healthcare-ai)
- [GDPR Compliance for Financial Services AI](https://www.areebi.com/compliance/gdpr/financial-services-ai)
- [GDPR Compliance for Legal AI](https://www.areebi.com/compliance/gdpr/legal-ai)
- [GDPR Compliance for Government AI](https://www.areebi.com/compliance/gdpr/government-ai)
- [EU AI Act Compliance for Healthcare AI](https://www.areebi.com/compliance/eu-ai-act/healthcare-ai)
- [EU AI Act Compliance for Financial Services AI](https://www.areebi.com/compliance/eu-ai-act/financial-services-ai)
- [EU AI Act Compliance for Legal AI](https://www.areebi.com/compliance/eu-ai-act/legal-ai)
- [EU AI Act Compliance for Government AI](https://www.areebi.com/compliance/eu-ai-act/government-ai)
- [EU AI Act Compliance for Insurance AI](https://www.areebi.com/compliance/eu-ai-act/insurance-ai)
- [SOC 2 Compliance for Insurance AI](https://www.areebi.com/compliance/soc-2/insurance-ai)
- [GDPR Compliance for Insurance AI](https://www.areebi.com/compliance/gdpr/insurance-ai)
- [HIPAA Compliance for Insurance AI](https://www.areebi.com/compliance/hipaa/insurance-ai)
- [EU AI Act Compliance for Technology AI](https://www.areebi.com/compliance/eu-ai-act/technology-ai)
- [SOC 2 Compliance for Technology AI](https://www.areebi.com/compliance/soc-2/technology-ai)
- [GDPR Compliance for Technology AI](https://www.areebi.com/compliance/gdpr/technology-ai)

### Learn (AI Governance 101)
- [What is AI Governance?](https://www.areebi.com/learn/what-is-ai-governance)
- [What is Shadow AI?](https://www.areebi.com/learn/what-is-shadow-ai)
- [What is AI DLP?](https://www.areebi.com/learn/what-is-ai-dlp)
- [What is Prompt Injection?](https://www.areebi.com/learn/what-is-prompt-injection)
- [What is an AI Firewall?](https://www.areebi.com/learn/what-is-ai-firewall)
- [What is AI Compliance?](https://www.areebi.com/learn/what-is-ai-compliance)
- [What is Algorithmic Discrimination?](https://www.areebi.com/learn/what-is-algorithmic-discrimination)
- [What is AI Risk Management?](https://www.areebi.com/learn/what-is-ai-risk-management)
- [What is AI Transparency?](https://www.areebi.com/learn/what-is-ai-transparency)
- [What is Automated Decision-Making?](https://www.areebi.com/learn/what-is-automated-decision-making)
- [What is an AI Audit?](https://www.areebi.com/learn/what-is-ai-audit)
- [What is Responsible AI?](https://www.areebi.com/learn/what-is-responsible-ai)
- [What is AI Bias Testing?](https://www.areebi.com/learn/what-is-ai-bias-testing)
- [What is AI Observability?](https://www.areebi.com/learn/what-is-ai-observability)
- [What is AI Compliance Automation?](https://www.areebi.com/learn/what-is-ai-compliance-automation)
- [What is an AI Policy Engine?](https://www.areebi.com/learn/what-is-ai-policy-engine)
- [What is an AI Control Plane?](https://www.areebi.com/learn/what-is-ai-control-plane)
- [What is Adversarial Robustness?](https://www.areebi.com/learn/what-is-adversarial-robustness)
- [What is Model Drift?](https://www.areebi.com/learn/what-is-model-drift)
- [What is Data Poisoning?](https://www.areebi.com/learn/what-is-data-poisoning)
- [What is Differential Privacy?](https://www.areebi.com/learn/what-is-differential-privacy)
- [What is AI Red Teaming?](https://www.areebi.com/learn/what-is-ai-red-teaming)
- [What are Model Cards?](https://www.areebi.com/learn/what-is-model-cards)
- [What is Federated Learning Security?](https://www.areebi.com/learn/what-is-federated-learning-security)
- [What is AI Supply Chain Security?](https://www.areebi.com/learn/what-is-ai-supply-chain-security)
- [What is AI Incident Response?](https://www.areebi.com/learn/what-is-ai-incident-response)
- [What is AI Vendor Risk?](https://www.areebi.com/learn/what-is-ai-vendor-risk)
- [What is Data Residency for AI?](https://www.areebi.com/learn/what-is-data-residency-for-ai)
- [What is AI Runtime Policy?](https://www.areebi.com/learn/what-is-ai-runtime-policy)
- [What is Prompt Engineering Security?](https://www.areebi.com/learn/what-is-prompt-engineering-security)
- [What is AI Rate Limiting?](https://www.areebi.com/learn/what-is-ai-rate-limiting)
- [What is Agent Governance?](https://www.areebi.com/learn/what-is-agent-governance)
- [What is AI Attribution?](https://www.areebi.com/learn/what-is-ai-attribution)
- [What is Retrieval-Augmented Generation (RAG)?](https://www.areebi.com/learn/what-is-rag)
- [What is LLM Fine-Tuning?](https://www.areebi.com/learn/what-is-fine-tuning)
- [What is Agentic AI?](https://www.areebi.com/learn/what-is-agentic-ai)
- [What is a Private LLM?](https://www.areebi.com/learn/what-is-a-private-llm)
- [What is an LLM Gateway?](https://www.areebi.com/learn/what-is-an-llm-gateway)
- [What is LLM Security?](https://www.areebi.com/learn/what-is-llm-security)
- [What is RAG Security?](https://www.areebi.com/learn/what-is-rag-security)
- [What is AI TRiSM?](https://www.areebi.com/learn/what-is-ai-trism)
- [What is an Enterprise LLM?](https://www.areebi.com/learn/what-is-an-enterprise-llm)

### Integrations
- [OpenAI / GPT](https://www.areebi.com/integrations/openai)
- [Anthropic / Claude](https://www.areebi.com/integrations/anthropic)
- [Azure OpenAI Service](https://www.areebi.com/integrations/azure-openai)
- [Google Vertex AI](https://www.areebi.com/integrations/google-vertex)
- [Ollama (Local LLMs)](https://www.areebi.com/integrations/ollama)
- [AWS Bedrock](https://www.areebi.com/integrations/aws-bedrock)
- [Okta](https://www.areebi.com/integrations/okta)
- [Microsoft Entra ID](https://www.areebi.com/integrations/azure-ad)
- [Hugging Face](https://www.areebi.com/integrations/hugging-face)
- [OpenRouter](https://www.areebi.com/integrations/openrouter)
- [Together AI](https://www.areebi.com/integrations/together-ai)
- [LM Studio](https://www.areebi.com/integrations/lm-studio)
- [LocalAI](https://www.areebi.com/integrations/localai)
- [KoboldCPP](https://www.areebi.com/integrations/koboldcpp)
- [Google Gemini](https://www.areebi.com/integrations/google-gemini)
- [Cohere](https://www.areebi.com/integrations/cohere)
- [Mistral AI](https://www.areebi.com/integrations/mistral-ai)
- [Groq](https://www.areebi.com/integrations/groq)
- [DeepSeek](https://www.areebi.com/integrations/deepseek)
- [NVIDIA NIM](https://www.areebi.com/integrations/nvidia-nim)
- [Fireworks AI](https://www.areebi.com/integrations/fireworks-ai)
- [Perplexity AI](https://www.areebi.com/integrations/perplexity-ai)
- [TrueFoundry](https://www.areebi.com/integrations/truefoundry)

### Use Cases
- [AI Governance for Code Generation](https://www.areebi.com/use-cases/code-generation)
- [AI Governance for Customer Support Automation](https://www.areebi.com/use-cases/customer-support)
- [AI Governance for Document Analysis](https://www.areebi.com/use-cases/document-analysis)
- [AI Governance for Research & Development](https://www.areebi.com/use-cases/research-development)
- [AI Governance for Compliance Automation](https://www.areebi.com/use-cases/compliance-automation)
- [AI Governance for Internal Knowledge Management](https://www.areebi.com/use-cases/internal-knowledge-management)
- [AI Governance for HR & Recruiting](https://www.areebi.com/use-cases/hr-recruiting)
- [AI Governance for Marketing Teams](https://www.areebi.com/use-cases/marketing)
- [AI Governance for Sales Teams](https://www.areebi.com/use-cases/sales)
- [AI Governance for Financial Analysis](https://www.areebi.com/use-cases/financial-analysis)
- [AI Governance for Data Analytics & Business Intelligence](https://www.areebi.com/use-cases/data-analytics)
- [AI Governance for Finance & Accounting Teams](https://www.areebi.com/use-cases/finance-accounting)
- [AI Governance for Executive Communications](https://www.areebi.com/use-cases/executive-communications)
- [AI Governance for Supply Chain & Procurement](https://www.areebi.com/use-cases/supply-chain)
- [AI Governance for IT Operations & DevOps](https://www.areebi.com/use-cases/it-operations)

### Comparisons
- [Manual AI Governance vs Automation: True Cost](https://www.areebi.com/compare/manual-ai-governance)
- [Areebi vs Point Solutions (DLP-Only Tools)](https://www.areebi.com/compare/point-solutions)
- [Areebi vs Platform Bundles (Cisco, Palo Alto)](https://www.areebi.com/compare/platform-bundles)
- [Areebi vs DIY / Open Source AI Governance](https://www.areebi.com/compare/diy-open-source)
- [Best AI Governance Tools & Platforms for 2026](https://www.areebi.com/compare/best-ai-governance-tools-2026)
- [Areebi vs Lakera (Now Check Point AI Security)](https://www.areebi.com/compare/lakera)
- [Areebi vs Protecto.ai](https://www.areebi.com/compare/protecto-ai)
- [Areebi vs Prompt Security (Now SentinelOne Singularity)](https://www.areebi.com/compare/prompt-security)
- [Areebi vs Wald.ai](https://www.areebi.com/compare/wald-ai)
- [Areebi vs Nightfall AI](https://www.areebi.com/compare/nightfall-ai)
- [Areebi vs Microsoft Purview AI Hub](https://www.areebi.com/compare/microsoft-purview-ai)
- [Areebi vs Robust Intelligence](https://www.areebi.com/compare/robust-intelligence)
- [Areebi vs Cisco AI Defense: Complete Comparison for 2026](https://www.areebi.com/compare/cisco-ai-defense)
- [Areebi vs Palo Alto AI Security: Which Is Right for Your Organization?](https://www.areebi.com/compare/palo-alto-ai-security)
- [Areebi vs Netskope for AI Governance: A Detailed Comparison](https://www.areebi.com/compare/netskope-ai-governance)
- [NIST AI RMF vs ISO/IEC 42001: Which AI Framework Should You Adopt?](https://www.areebi.com/compare/nist-ai-rmf-vs-iso-42001)
- [Areebi vs Fairly AI: AI Control Plane vs Model Risk Management](https://www.areebi.com/compare/areebi-vs-fairly-ai)
- [Areebi vs Monitaur: AI Control Plane vs Model Governance and Assurance](https://www.areebi.com/compare/areebi-vs-monitaur)
- [Build vs Buy AI Governance: Honest TCO and Decision Framework](https://www.areebi.com/compare/build-vs-buy-ai-governance)
- [Areebi vs Credal: 2026 AI Security Platform Comparison](https://www.areebi.com/compare/credal)
- [Areebi vs Wiz AI Security Posture Management (AI-SPM): 2026 Comparison](https://www.areebi.com/compare/wiz-ai-spm)
- [Areebi vs 6clicks: Runtime AI Control Plane vs GRC Platform (Australia)](https://www.areebi.com/compare/areebi-vs-6clicks)
- [Areebi vs Redactive: Secure AI Control Plane vs Permissions-Aware AI Data Layer (Australia)](https://www.areebi.com/compare/areebi-vs-redactive)
- [Best AI Governance and Security Platforms for Australian Regulated Enterprises (2026)](https://www.areebi.com/compare/best-ai-governance-platform-australia-2026)
- [AnythingLLM vs LibreChat: Honest Technical Comparison (2026)](https://www.areebi.com/compare/anythingllm-vs-librechat)
- [AnythingLLM vs Open WebUI: Honest Comparison + Licence Facts (2026)](https://www.areebi.com/compare/anythingllm-vs-open-webui)
- [Areebi vs AnythingLLM: The Engine and the Governed Platform (2026)](https://www.areebi.com/compare/areebi-vs-anythingllm)
- [ChatGPT Enterprise Alternatives: 9 Real Options for 2026](https://www.areebi.com/compare/chatgpt-enterprise-alternatives)
- [EU AI Act vs NIST AI RMF: Clause-by-Clause Comparison](https://www.areebi.com/compare/eu-ai-act-vs-nist-ai-rmf)
- [EU AI Act vs GDPR: Clause-by-Clause Comparison](https://www.areebi.com/compare/eu-ai-act-vs-gdpr)
- [ISO 42001 vs SOC 2: Clause-by-Clause Comparison](https://www.areebi.com/compare/iso-42001-vs-soc-2)
- [ISO 42001 vs EU AI Act: Clause-by-Clause Comparison](https://www.areebi.com/compare/iso-42001-vs-eu-ai-act)
- [EU AI Act vs Colorado AI Act: Clause-by-Clause Comparison](https://www.areebi.com/compare/eu-ai-act-vs-colorado-ai-act)
- [Colorado AI Act vs NYC LL144: Clause-by-Clause Comparison](https://www.areebi.com/compare/colorado-ai-act-vs-nyc-local-law-144)
- [NIST AI RMF vs NIST GenAI Profile: Clause-by-Clause Comparison](https://www.areebi.com/compare/nist-ai-rmf-vs-generative-ai-profile)
- [HIPAA vs GDPR: Clause-by-Clause Comparison](https://www.areebi.com/compare/hipaa-vs-gdpr-for-ai)
- [SOC 2 vs FedRAMP: Clause-by-Clause Comparison](https://www.areebi.com/compare/soc-2-vs-fedramp-for-ai)
- [ISO 42001 vs GDPR: Clause-by-Clause Comparison](https://www.areebi.com/compare/iso-42001-vs-gdpr)
- [NIST AI RMF vs Singapore MGF: Clause-by-Clause Comparison](https://www.areebi.com/compare/nist-ai-rmf-vs-singapore-model-ai-governance)
- [SOC 2 vs HIPAA: Clause-by-Clause Comparison](https://www.areebi.com/compare/soc-2-vs-hipaa-for-ai)

### Blog
- [Shadow AI Detection: How to Detect Unsanctioned AI (2026 Guide)](https://www.areebi.com/resources/blog/shadow-ai-detection-guide)
- [ChatGPT Enterprise Pricing in 2026: The Complete Cost Breakdown](https://www.areebi.com/resources/blog/chatgpt-enterprise-pricing-breakdown)
- [Self-Hosted LLM for Business: The Realistic 2026 Guide](https://www.areebi.com/resources/blog/self-hosted-llm-for-business)
- [On-Premise AI Chatbot Buyer's Guide (2026)](https://www.areebi.com/resources/blog/on-premise-ai-chatbot-buyers-guide)
- [AnythingLLM Enterprise Guide: Deployment, Hosting, and Hardening (2026)](https://www.areebi.com/resources/blog/anythingllm-enterprise-guide)
- [Open WebUI Enterprise License Explained: The 50-User Branding Clause (2026)](https://www.areebi.com/resources/blog/open-webui-enterprise-license-explained)
- [LibreChat for Business: What It Does Well and the Governance Gaps (2026)](https://www.areebi.com/resources/blog/librechat-for-business)
- [Is ChatGPT Safe for Business? An Evidence-Led 2026 Review](https://www.areebi.com/resources/blog/is-chatgpt-safe-for-business)
- [The Complete AI Acceptable Use Policy Guide (2026)](https://www.areebi.com/resources/blog/ai-acceptable-use-policy-guide)
- [AI Data Sovereignty in Australia: The 2026 Practical Guide](https://www.areebi.com/resources/blog/ai-data-sovereignty-australia)
- [NIST AI RMF MAP Function: Deep Dive for CISOs (2026)](https://www.areebi.com/resources/blog/nist-ai-rmf-map-function-deep-dive)
- [NIST AI RMF MANAGE Function: Deep Dive for CISOs (2026)](https://www.areebi.com/resources/blog/nist-ai-rmf-manage-function-deep-dive)
- [Solving Brand Confusion in AI Security: Lessons from Search Misspellings](https://www.areebi.com/resources/blog/solving-brand-confusion-ai-security-misspellings)
- [The Real Cost of One Shadow-AI Data Breach (2026 Models)](https://www.areebi.com/resources/blog/cost-of-one-shadow-ai-breach-2026)
- [Governing GenAI in Healthcare Operations: A Compliance-First Playbook](https://www.areebi.com/resources/blog/governing-genai-healthcare-operations-2026)
- [The Real Cost of a Toxic AI Vendor Backlink Profile (2026 Case Notes)](https://www.areebi.com/resources/blog/toxic-ai-vendor-backlink-profile-2026)
- [State of AI Governance: May 2026 Roundup](https://www.areebi.com/resources/blog/state-of-ai-governance-may-2026)
- [The CISO's AI Governance Playbook: 30/60/90 Day Plan](https://www.areebi.com/resources/blog/ciso-ai-governance-playbook-30-60-90)
- [Prompt Injection 2026: A Defender's Deep Dive](https://www.areebi.com/resources/blog/prompt-injection-deep-dive-2026)
- [The AI Red Team You Don't Have Yet (And How To Start)](https://www.areebi.com/resources/blog/ai-red-team-you-dont-have-2026)
- [FedRAMP 20x and What It Means for AI Vendors in 2026](https://www.areebi.com/resources/blog/fedramp-20x-impact-ai-vendors-2026)
- [ISO/IEC 42001 Certification: A 12-Month Roadmap](https://www.areebi.com/resources/blog/iso-42001-certification-12-month-roadmap)
- [DORA + AI: What Financial Institutions Need to Know by 2026](https://www.areebi.com/resources/blog/dora-ai-financial-institutions-2026)
- [Build vs Buy: The AI Governance Platform Decision (2026)](https://www.areebi.com/resources/blog/build-vs-buy-ai-governance-platform-2026)
- [AI Agent Monitoring 101: Observability Beyond Prompts](https://www.areebi.com/resources/blog/ai-agent-monitoring-observability-2026)
- [Australian Privacy Act 2026: A CISO's Checklist](https://www.areebi.com/resources/blog/australian-privacy-act-2026-ciso-checklist)
- [The 90-Minute Shadow AI Hunt Playbook (2026)](https://www.areebi.com/resources/blog/90-minute-shadow-ai-hunt-playbook)
- [OMB M-24-18 Federal Contractor AI Compliance Checklist (2026)](https://www.areebi.com/resources/blog/omb-m-24-18-federal-contractor-checklist)
- [OpenAI Enterprise + AI Governance: A CISO's Guide (2026)](https://www.areebi.com/resources/blog/openai-enterprise-ai-governance-ciso-guide)
- [Anthropic Claude + Areebi: An Architecture Walkthrough (2026)](https://www.areebi.com/resources/blog/anthropic-claude-areebi-architecture-walkthrough)
- [The AI Vendor List Your CFO Asked For (And How to Build It) - 2026](https://www.areebi.com/resources/blog/ai-vendor-list-cfo-2026)
- [Singapore AI Verify in 2026: Implementation Notes for ASEAN Buyers](https://www.areebi.com/resources/blog/singapore-ai-verify-implementation-2026)
- [Manufacturing AI Operations: Trade Secret Protection in 2026](https://www.areebi.com/resources/blog/manufacturing-ai-trade-secret-protection-2026)
- [Insurance Underwriting AI: A Governance Framework for Actuaries (2026)](https://www.areebi.com/resources/blog/insurance-underwriting-ai-actuarial-governance-2026)
- [GDPR + Generative AI: The EDPB Opinion 28/2024 Implementation Playbook for CISOs](https://www.areebi.com/resources/blog/gdpr-generative-ai-edpb-opinion-28-2024-playbook)
- [AI Bill of Materials (AIBOM): What NTIA, NIST, and EO 14110 Require - and What to Ship Now](https://www.areebi.com/resources/blog/aibom-ai-bill-of-materials-nist-eo-14110-playbook)
- [SOC 2 + AI Workloads: How the Trust Services Criteria Actually Map to LLM Systems](https://www.areebi.com/resources/blog/soc-2-ai-workloads-trust-services-criteria-mapping)
- [HIPAA + Clinical AI: The 2026 Playbook for PHI in LLM Systems](https://www.areebi.com/resources/blog/hipaa-clinical-ai-protected-health-information-2026-playbook)
- [Open source LLMs vs proprietary models: the 2026 enterprise governance reality](https://www.areebi.com/resources/blog/open-source-ai-vs-proprietary-llm-enterprise-governance-2026)
- [AI incident response runbook: the 2026 playbook for prompt injection, model drift, and DLP breaches](https://www.areebi.com/resources/blog/ai-incident-response-runbook-2026)
- [Fine-tuning vs RAG vs prompt engineering: the 2026 compliance trade-off matrix](https://www.areebi.com/resources/blog/llm-fine-tuning-vs-rag-compliance-tradeoffs-2026)
- [AI Control Plane RFP template: the 87-question buyer's checklist for 2026](https://www.areebi.com/resources/blog/ai-control-plane-rfp-template-2026)
- [The 1-year AI governance retrospective: a template CISOs can actually use](https://www.areebi.com/resources/blog/ai-governance-program-1-year-retrospective-template-2026)
- [Quarterly AI governance board reporting: the 2026 template](https://www.areebi.com/resources/blog/board-reporting-ai-governance-quarterly-template-2026)
- [Cybersecurity insurance + AI: what's covered, what's excluded, what to demand in 2026](https://www.areebi.com/resources/blog/cybersecurity-insurance-ai-coverage-exclusions-2026)
- [Generative AI vendor risk questionnaire template: the 60-question 2026 update](https://www.areebi.com/resources/blog/procurement-vrq-questionnaire-template-genai-saas-2026)
- [The 2026 AI Governance OKR Template: 12 Quarterly Objectives Every CISO Should Consider](https://www.areebi.com/resources/blog/ai-governance-okr-template-2026)
- [FDA AI/ML-Enabled Medical Devices + SaMD + Clinical Decision Support: The 2026 Governance Playbook](https://www.areebi.com/resources/blog/fda-ai-medical-device-samd-clinical-decision-support-2026)
- [Legal AI: Protecting Attorney-Client Privilege + Work Product in 2026](https://www.areebi.com/resources/blog/legal-services-ai-privilege-work-product-2026)
- [Year-End 2026: The 30-Item AI Governance Checklist Before Fiscal Year-End](https://www.areebi.com/resources/blog/year-end-2026-ai-governance-priorities-checklist)
- [NIST AI RMF GOVERN Function: Deep Dive for CISOs (2026)](https://www.areebi.com/resources/blog/nist-ai-rmf-govern-function-deep-dive)
- [The AI Control Plane: The Enterprise Guide to Centralized AI Management](https://www.areebi.com/resources/blog/ai-control-plane-enterprise-guide)
- [The ROI of AI Governance: Building the Business Case for Your CFO](https://www.areebi.com/resources/blog/ai-governance-roi-business-case)
- [Introducing Areebi: The AI Control Plane Built for Mid-Market Enterprise](https://www.areebi.com/resources/blog/areebi-platform-launch-april-2026)
- [Getting Started with Areebi: A 30-Day Implementation Guide](https://www.areebi.com/resources/blog/getting-started-areebi-implementation-guide)
- [The Global AI Compliance Landscape in 2026: Every Law You Need to Know](https://www.areebi.com/resources/blog/ai-compliance-landscape-2026)
- [AI Control Plane vs AI Gateway: What's the Difference and Which Do You Need?](https://www.areebi.com/resources/blog/ai-control-plane-vs-ai-gateway)
- [Prompt Injection Prevention for Enterprise AI: A Complete Defense Guide](https://www.areebi.com/resources/blog/prompt-injection-prevention-enterprise)
- [Healthcare AI Governance: The 2026 CISO's Guide to HIPAA-Compliant AI](https://www.areebi.com/resources/blog/healthcare-ai-governance-ciso-guide-2026)
- [Colorado AI Act 2026: What Enterprises Must Do Before June 30](https://www.areebi.com/resources/blog/colorado-ai-act-what-to-know)
- [How to Build an Enterprise AI Control Plane: A Step-by-Step Guide](https://www.areebi.com/resources/blog/building-enterprise-ai-control-plane)
- [AI Red Teaming: The Enterprise Guide to Adversarial Testing of LLMs](https://www.areebi.com/resources/blog/ai-red-teaming-guide)
- [NIST AI RMF Implementation: A Practical Guide for Enterprise Teams](https://www.areebi.com/resources/blog/nist-ai-rmf-implementation-guide)
- [How an AI Control Plane Automates Compliance Across Every Framework](https://www.areebi.com/resources/blog/ai-control-plane-compliance-automation)
- [UK AI Regulation in 2026: Principles, Regulators, and What to Expect](https://www.areebi.com/resources/blog/uk-ai-regulation-guide)
- [AI Model Supply Chain Security: Protecting Enterprise AI from Third-Party Risk](https://www.areebi.com/resources/blog/model-supply-chain-security)
- [ISO 42001 Certification for AI: Requirements, Timeline, and Cost](https://www.areebi.com/resources/blog/iso-42001-certification-guide)
- [What Is Shadow AI? The Complete Enterprise Guide](https://www.areebi.com/resources/blog/what-is-shadow-ai)
- [The 10 Most Dangerous LLM Attack Vectors in 2026](https://www.areebi.com/resources/blog/llm-attack-vectors-2026)
- [Australia Privacy Act Amendments 2026: AI Automated Decision-Making Rules](https://www.areebi.com/resources/blog/australia-ai-privacy-act-2026)
- [Data Poisoning Attacks on Enterprise AI: Detection and Defense Strategies](https://www.areebi.com/resources/blog/data-poisoning-enterprise-defense)
- [Enterprise AI Compliance Checklist: 50 Controls Across 12 Frameworks](https://www.areebi.com/resources/blog/ai-compliance-checklist-enterprise)
- [US State AI Laws: Navigating the Patchwork of 2026 Regulations](https://www.areebi.com/resources/blog/us-state-ai-laws-patchwork)
- [EU AI Act Compliance: What Mid-Market Companies Need to Know](https://www.areebi.com/resources/blog/eu-ai-act-compliance-mid-market)
- [Why AI Security Is Not Just Application Security: What CISOs Need to Know](https://www.areebi.com/resources/blog/ai-security-vs-traditional-appsec)
- [Singapore's Agentic AI Governance Framework: First in the World](https://www.areebi.com/resources/blog/singapore-agentic-ai-governance)
- [AI Governance vs AI Compliance: Understanding the Difference](https://www.areebi.com/resources/blog/ai-governance-vs-ai-compliance)
- [AI Governance vs AI Security: What's the Difference?](https://www.areebi.com/resources/blog/ai-governance-vs-ai-security)
- [The True Cost of Ungoverned AI: A 2026 Analysis](https://www.areebi.com/resources/blog/cost-of-ungoverned-ai)
- [How to Build an AI Governance Program from Scratch](https://www.areebi.com/resources/blog/build-ai-governance-program)

### Templates
- [The CISO's AI Security Policy Checklist](https://www.areebi.com/resources/templates/ai-security-policy-checklist)
- [Enterprise AI Acceptable Use Policy Template](https://www.areebi.com/resources/templates/ai-acceptable-use-policy-template)
- [AI Vendor Risk Assessment Questionnaire](https://www.areebi.com/resources/templates/ai-vendor-risk-assessment-questionnaire)
- [Shadow AI Discovery & Remediation Playbook](https://www.areebi.com/resources/templates/shadow-ai-discovery-playbook)
- [AI Risk Register Template](https://www.areebi.com/resources/templates/ai-risk-register-template)
- [EU AI Act Compliance Checklist](https://www.areebi.com/resources/templates/eu-ai-act-compliance-checklist)
- [Australian Privacy Act ADM Compliance Checklist](https://www.areebi.com/resources/templates/australian-privacy-act-compliance-checklist)
- [NIST AI RMF Checklist 2026 (54 Controls)](https://www.areebi.com/resources/templates/nist-ai-rmf-implementation-checklist)
- [AI Data Classification Framework Template](https://www.areebi.com/resources/templates/ai-data-classification-framework)
- [AI Incident Response Plan Template](https://www.areebi.com/resources/templates/ai-incident-response-plan-template)
- [Board AI Risk Reporting Template](https://www.areebi.com/resources/templates/board-ai-risk-reporting-template)
- [ISO 42001 Gap Analysis Checklist](https://www.areebi.com/resources/templates/iso-42001-gap-analysis-checklist)

### Research
- [The Australian AI Data-Governance Index 2026](https://www.areebi.com/resources/research/australian-ai-data-governance-2026)

### Tools
- [Would This Leak? Shadow AI Prompt Challenge - 10 real prompts, 3 of them safe, no signup](https://www.areebi.com/tools/would-this-leak)
- [Privacy Act ADM Transparency Readiness Checker](https://www.areebi.com/tools/privacy-act-adm-readiness-checker)
- [APRA CPS 230 AI Gap Analyzer](https://www.areebi.com/tools/apra-cps-230-ai-gap-analyzer)
- [APRA CPS 234 AI Security Checker](https://www.areebi.com/tools/apra-cps-234-ai-security-checker)
- [Sovereign AI Readiness Checker](https://www.areebi.com/tools/sovereign-ai-readiness-checker)

### Reference
- [Australian AI Regulation Tracker](https://www.areebi.com/resources/ai-regulation-tracker)
- [AI Governance Framework Matrix - 12 frameworks x 15 dimensions, clause-cited, CC BY 4.0](https://www.areebi.com/resources/ai-framework-matrix)
  - Machine-readable: https://www.areebi.com/ai-framework-matrix.json (JSON) and https://www.areebi.com/ai-framework-matrix.csv (CSV)

## Contact
- Website: https://www.areebi.com
- Email: hello@areebi.com
- Demo: https://www.areebi.com/demo
- Free trial: https://www.areebi.com/free-trial
- Free AI Risk Assessment: https://www.areebi.com/assessment