Insights on AI governance, enterprise AI security, and the future of monitored AI.
Our first production release. A self-hosted AI firewall for every AI interaction in your enterprise — cloud, on-prem, or fully air-gapped — with guardrails, DLP, cost metering, and a tamper-evident audit trail.
Retention floors run from six months to six years, and you find out which one applies to you after the incident. Why audit log retention shouldn't be a pricing tier — and what we changed.
LLM costs scale silently until the invoice arrives. Apply FinOps to AI — real-time metering, budgets, caching, model routing, and chargeback — to keep spend under control.
The EU AI Act is now in force. A practical checklist through the risk tiers, obligations, and the controls you need to demonstrate AI compliance in 2026.
Prompt injection is the top security risk for LLM apps. How direct and indirect attacks work, why they are hard to stop, and the architecture-level defenses that contain them.
AI firewalls are a new product category that sits between your employees and AI providers. Learn what they do, why traditional firewalls don't cover AI, and how to evaluate one.
Employees are using AI tools without oversight, and it's costing you more than you think. Learn how to audit your AI spending and gain visibility into shadow AI usage.
PII, source code, financial data, and internal documents are being sent to external AI providers every day. Here are 5 real-world scenarios and how to prevent each one.
63% of organizations can't control their AI usage. Shadow AI is the hidden security threat every enterprise faces. Learn how to detect it and bring it under governance.
A complete framework for IT directors — the 5 pillars of AI governance, regulatory landscape, implementation steps, KPIs, and a 30-day getting started plan.
You can govern AI without surveillance. Learn the difference between monitoring and spying, what metadata to track, and how to build trust while maintaining control.
MSPs and holding companies need genuine tenant isolation, not one deployment per client. What real multi-tenant AI governance requires — isolated policy, audit trails, and billing.
Fully offline AI is real and verifiable. How air-gapped deployments actually work, who genuinely needs one, and the tradeoffs versus a cloud-connected gateway.
Most companies can't answer what they actually spend on AI. A framework for quantifying shadow spend and calculating the real ROI of a governed AI gateway.
A copy-paste-ready AI acceptable use policy template, plus the rollout guide — what to include, what to customize, and how to make it actually enforceable.
Traditional DLP was built to stop file exfiltration, not inspect AI API traffic. Why legacy tools miss AI data leakage, and what purpose-built AI DLP looks like.