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Reload the pagePractical analysis, compliance guides, and technical deep dives from the team building the Areebi platform. Stay current on shadow AI prevention, regulatory changes, and enterprise AI security best practices.
Subscribe via RSSA practical guide to shadow AI detection: the five detection-signal families (network and DNS, SaaS billing, identity and OAuth, endpoint and browser, collaboration apps), the detection tooling landscape (CASB, DLP, SSPM, browser governance, purpose-built AI security), how to build a continuous detection programme, the metrics to track, and the block-versus-govern decision. Cited primary sources: IBM Cost of a Data Breach 2025, Cyberhaven, Harmonic Security, Varonis, Gartner.
The definitive 2026 breakdown of ChatGPT Enterprise pricing: reported per-seat costs ($45-$75/user/month), the 150-seat minimum, the new credits-based flexible pricing model, hidden costs, and a sourced TCO comparison against Microsoft 365 Copilot, Claude Enterprise, and private deployment at 100, 250, and 500 seats. Every number cited.
A practical, opinionated guide to self-hosting a large language model for business in 2026 - why businesses self-host (data control, residency, cost at scale), the realistic stack options (Ollama, vLLM, AnythingLLM, LibreChat, Open WebUI) in one comparison table, hardware sizing, the hidden operational costs DIY estimates omit, and when a managed private deployment beats building it yourself.
A buyer's guide for selecting an on-premise or private AI chatbot for business in 2026 - a requirements checklist, an evaluation criteria table across security, deployment, model support, and governance, the questions to ask every vendor, the red flags that should end an evaluation, and a TCO worksheet that captures the costs vendors leave out.
A definitive guide to running AnythingLLM in an enterprise: Docker, Kubernetes and desktop deployment, multi-user setup, the real enterprise-readiness gaps in the raw open-source build (audit depth, DLP, policy enforcement, SSO enforcement), the hosting landscape, a hardening checklist, and where a governed platform fits. Facts verified June 2026.
A factual, neutral explanation of the Open WebUI licence: what changed and when, the exact branding-protection clause, the 50-user / 30-day threshold that triggers the enterprise requirement, what the enterprise licence provides, and the realistic options for organisations - comply, license, or move to an alternative. Verified against the official LICENSE and docs, June 2026.
A practical guide to deploying LibreChat in a business: what it genuinely does well (multi-provider chat, strong enterprise auth, spend controls, agents and MCP), the requirements for a production business deployment, the governance gaps you must plan around (DLP, immutable audit, policy enforcement, compliance evidence), and how it compares to other open-source options. Facts verified June 2026.
A balanced, evidence-led answer to whether ChatGPT is safe for business in 2026. What OpenAI does with consumer versus Team/Business and Enterprise data, the real incidents (Samsung, the March 2023 chat-history bug), the leakage statistics (Cyberhaven, Harmonic), a risk-by-tier table, a controls checklist for safe use, and when a private deployment is the right answer. Verdict: yes, with conditions. Every statistic cited.
The most complete free guide to writing an AI acceptable use policy in 2026. Why every company needs one now, the 12 sections every AI AUP must contain - each with real, copy-ready example policy language - industry variations for healthcare and financial services, a rollout playbook, and the common failure modes. Includes a free downloadable template and a policy generator. Sources cited.
A practical 2026 guide to AI data sovereignty in Australia: what sovereignty means for AI workloads under Australian law, the 2025-2026 trigger events (the DeepSeek government-device ban, APRA's April 2026 AI letter, GovAI Chat on IRAP-assessed infrastructure, ACSC guidance), where popular AI tools actually process Australian data, the sovereignty options ladder, and a compliance mapping. Sources cited.
A CISO-focused deep dive into the NIST AI RMF MAP function and its five subcategories (MAP 1-5). Concrete context-setting, risk categorization, capability documentation, impact mapping, and risk tolerance workflows, mapped to Areebi platform capabilities and authoritative source documents (NIST AI 100-1, AI 600-1, OMB M-24-10, EO 14110, ISO/IEC 42001).
A CISO-focused deep dive into the NIST AI RMF MANAGE function and its four subcategories (MANAGE 1-4). Concrete risk prioritization and response, resource allocation, risk communication, and continuous improvement workflows, mapped to Areebi platform capabilities and authoritative source documents (NIST AI 100-1, AI 600-1, OMB M-24-10, EO 14110, ISO/IEC 42001).