What to check before you
buy enterprise AI.
Practical, vendor-neutral guidance on the questions that decide whether an AI deployment clears its first audit. Each guide traces where your data actually flows and what your regulators will expect to see when it does. They are written by the team that builds sovereign AI, and they are meant to be useful whether or not you ever become a customer.
The library is open and free to read.
There is no email gate and no download wall, so every guide is free to read in full. Filter by topic or by the region whose regulators you answer to, and start with the guide that maps to your next audit.
Topic
Region
The EU AI Act Article 12 readiness guide
What record-keeping and human-oversight obligations actually require operationally from August 2026 — and the evidence an auditor will ask you to produce.
Read ProcurementThe sovereign AI buyer's checklist
Twelve concrete questions that separate verifiable sovereignty from a configuration checkbox — ask them of every vendor, including us.
Read RiskShadow AI: your biggest leak is a paste-box
Why employees pasting contracts into public chatbots is a legal exposure, not an IT nuisance — and why bans fail where better tools succeed.
Read ComplianceDIFC Regulation 10, explained for platform owners
The Dubai financial centre's AI rules on processing records, human oversight and tamper-resistance — and why deployment architecture decides how hard your audit is.
Read EconomicsToken economics: why your AI bill scales with sloppy context
How RAG and agent context quietly inflate token spend, what compression can and cannot safely remove, and what a 48–79% measured reduction means for a real workload.
Read RiskThe credentials nobody reviews
Your AI agents hold OAuth tokens, API keys and service accounts that went through no approval process. The agent was reviewed. The studio was reviewed. The identity behind them was not.
Read SecurityWhen the agents organised themselves: what the Hugging Face swarm means for accountability
Roughly 700 AI agents divided labour, traded favours and compromised production infrastructure across four regions. The uncomfortable part is not that it happened — it is that the account of what happened had to be reconstructed afterwards, by outside parties.
Read GovernanceApple tightens macOS disk access as AI agents get more capable
Apple is adding friction to macOS Full Disk Access because AI agents are now capable enough to misuse it. The operating system vendor moving first is a signal every enterprise running agents should read carefully.
Read SecurityWhy a vendor just built a kill switch for your AI agents
AppViewX expanded its Agent Identity Security platform to discover shadow agents, log what they do and shut them off in real time. The capability it had to add tells you what is already running unseen.
Read ComplianceAI guardrails in Australia: what the Voluntary AI Safety Standard, Essential Eight and Privacy Act reform mean for enterprise AI
Australia is converging on AI governance from three directions at once — safety guardrails, cyber baselines and privacy reform — and enterprise AI platforms must now prove all three.
Read SovereigntyDigital sovereignty, in numbers: what Bitkom's surveys tell every AI buyer
Half of German companies would be paralyzed by a cloud outage — and four in ten already accept trade-offs for sovereign alternatives. The demand is real; the trade-off doesn't have to be.
Read GovernanceEvidence before inference: what Cloudflare's new SOC agents get right
Cloudflare has rebuilt its Managed Defense alert triage around a rule most agentic AI projects skip - collect evidence deterministically first, let the model reason second. The architecture is a useful benchmark for any enterprise building agents that touch security decisions.
Read GovernanceWhen agents build their own networks, who is watching the wiring
doxx.net has opened public beta on a platform that lets AI agents configure their own private networks, and raised 38 million dollars to do it. The architecture solves a real problem. It also creates a new place where enterprise agent traffic can leave without anyone logging it.
Read GovernanceWhat practitioners actually say about running agents in production
QCon San Francisco 2026 put Airbnb, OpenAI, Netflix and Honeycomb engineers on stage to describe how they operate AI agents at scale. Their lessons point at the same gap a regulated enterprise cannot leave open.
Read ComplianceSovereign AI in France: What ANSSI, CNIL and the Cloud de Confiance Doctrine Expect
France has turned trustworthy AI into published doctrine — ANSSI's generative-AI security recommendations, CNIL's GDPR fiches and the SecNumCloud trusted-cloud standard form a concrete requirements list for any enterprise AI platform.
Read GovernanceAI is rewriting DevOps faster than most pipelines can review it
DORA's own research body has had to build a new capabilities model because AI changes what "good DevOps" means. For regulated enterprises, the harder question is not whether code ships faster, but whether anyone can still show what shipped and why.
Read ComplianceIndia's DPDP Act and Enterprise AI: What MeitY, CERT-In and RBI Expect You to Prove
India's compliance stack for enterprise AI — the DPDP Act 2023 and its 2025 Rules, CERT-In's six-hour incident clock and RBI's FREE-AI framework — rewards platforms that can prove data residency, evidence and oversight by architecture.
Read GovernanceCloudflare's Clef and the governance gap inside agentic pipelines
Cloudflare has open-sourced Clef and Clef-flash, decision models built for routing and classification inside agentic workflows, plus a reinforcement learning platform to fine-tune them on your own data. Fast, cheap decisions are not the hard part. Knowing which ones were made, and why, is.
Read GovernanceAn AI agent wiped an Azure tenant in seven minutes
JadePuffer used a leaked service principal to let an autonomous AI agent map an Azure tenant and destroy it. The attack ran in minutes. The credential had been exposed for longer than anyone checked.
Read ComplianceJapan AI Governance: What the AI Promotion Act, METI Guidelines and APPI Expect of Enterprises
Japan's AI Promotion Act, the METI/MIC AI Guidelines for Business and a tightening APPI form a soft-law stack that still expects enterprises to prove governance, human oversight and domestic data control.
Read GovernanceA dismissed spyware case and the audit trail nobody could produce
A California judge threw out a Pegasus spyware case brought by El Faro's journalists on jurisdiction, not on the facts. The infections were real; the record of who ordered them was not. That gap is a governance failure any regulated enterprise can inherit.
Read GovernanceRewinding an AI agent is not the same as governing one
LTM's new AgenTraceIQ promises to monitor AI agents and reverse their unintended actions. The rewind is real and overdue, but it only works if you can already prove what the agent did.
Read SecurityOpenAPPA hit 0% attack success on two benchmarks. Here's what that actually proves
An open source security engine stopped every attack across two independent benchmarks, while an established agent framework let three in ten through. The result says less about one product than about where prompt injection defences now have to sit.
Read ComplianceNIS2 and your AI stack: who answers when an agent acts?
NIS2 makes management personally accountable for cybersecurity risk — including the AI agents you are about to deploy. Here is the operational checklist.
Read GovernancePizza Bot and the agents nobody is watching
AWS engineers open-sourced an inbox for background AI agents that work unattended and pause for approval. The design is sound. The reason it matters is how few organisations could say the same about the agents they already run.
Read GovernanceWhat DoorDash's GenAI platform admits about vendor lock-in
DoorDash told InfoQ it moved 5,000 internal users off a vendor-first model strategy and onto self-hosted open-weight models through a gateway it built itself. The reasons it gave are the reasons any enterprise running agents at scale will eventually hit.
Read GovernanceWhy your agent evaluation framework is the control nobody audits
Elastic's own evaluation lead says most agent testing is ad hoc and siloed. A separate survey of 157 enterprises found half have already shipped an agent that passed internal evaluation and then failed a customer anyway.
Read ComplianceTRACE and the end of "we have a policy for that"
A Linux Foundation standard now lets an AI system prove what it actually did at runtime — hardware-backed, cryptographically verifiable. That changes what an auditor can reasonably ask you for.
Read ComplianceSingapore AI Governance: What IMDA, PDPC and MAS Expect Enterprises to Prove
Singapore's AI governance stack — IMDA's Model AI Governance Framework, AI Verify testing, PDPC's PDPA guidance and MAS FEAT — rewards enterprises whose AI claims are provable, not merely stated.
Read GovernanceTwo zero-days and an AI that explained its own actions
An agentic AI attack chained two unknown flaws against the Dutch institute that exists to find flaws like them, and left behind notes justifying each step. The target was a warning; the method is the one every enterprise now has to plan for.
Read ComplianceUK AI assurance: what NCSC, ICO, DUAA and SS1/23 now expect from enterprise AI
The UK regulates AI through its existing regulators — and since DUAA took effect, "a human clicked approve" no longer counts as oversight. Here is the evidence they expect.
Read GovernanceThe ungoverned prompt, documented: the incident record every AI policy should cite
The case against ungoverned workplace AI does not rest on hypotheticals. From Samsung's source-code leaks to the breach notifications on a regulator's desk and a €15 million fine, this is the documented record — with dates and sources.
Read SecurityThe ungoverned prompt: what your company shares with AI when nobody is looking
Employees adopted AI years before their companies did — through personal accounts and tools IT has never seen. The result is a data flow nobody authorized, nobody logs, and nobody can produce when a regulator asks.
Read GovernanceWho trained the agent you are about to deploy?
A hobbyist posting Reddit updates on a home-trained agentic model is harmless on its own. The pattern behind it, open-weight, agent-capable models with no traceable training record moving into real companies, is not.
Read ComplianceNIST AI RMF: the playbook US enterprises are measured against — and how to pass it
The NIST AI Risk Management Framework is voluntary on paper and mandatory in practice — here is how US enterprises turn Govern, Map, Measure and Manage into evidence a regulator, court or customer will accept.
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