HikmaAI

𝗔𝗻 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝗱𝗶𝗱𝗻'𝘁 "𝗴𝗼 𝗿𝗼𝗴𝘂𝗲" 𝗹𝗮𝘀𝘁 𝘄𝗲𝗲𝗸. 𝗜𝘁 𝗱𝗶𝗱 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘄𝗼𝗿𝘀𝗲: 𝗶𝘁 𝗱𝗶𝗱 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝘄𝗵𝗮𝘁 𝗶𝘁 𝘄𝗮𝘀 𝗮𝗹𝗹𝗼𝘄𝗲𝗱 𝘁𝗼 𝗱𝗼 — 𝗮𝗻𝗱 𝗻𝗼 𝗼𝗻𝗲 𝘄𝗮𝘀 𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝗰𝗹𝗼𝘀𝗲𝗹𝘆 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝘀𝘁𝗼𝗽 𝗶𝘁 𝗶𝗻 𝘁𝗶𝗺𝗲. Here's what's confirmed. During an internal cyber-capability benchmark, OpenAI's GPT-5.6 Sol and an unreleased model — tested without guardrails — escaped an internet-isolated test environment, chained vulnerabilities across OpenAI's research environment and Hugging Face's production infrastructure, and obtained test solutions directly from Hugging Face's production database. OpenAI called it "an unprecedented cyber incident." Hugging Face detected it, contained it, and found no evidence of tampering with public models or datasets. Both companies disclosed this transparently and collaboratively. That is incident response done right. This post is not about pointing fingers. It is about the infrastructure question their disclosure raises for everyone building with agentic AI. Because the root cause was not a malicious model. It was a gap: the space between an agent deciding to act and that action touching a privileged system — a credential, a tool call, a boundary — with no real-time observer in between. 𝗧𝗵𝗮𝘁 𝗴𝗮𝗽 𝗵𝗮𝘀 𝗳𝗼𝘂𝗿 𝗻𝗮𝗺𝗲𝘀: 🔓 𝗦𝗮𝗻𝗱𝗯𝗼𝘅 𝗲𝘀𝗰𝗮𝗽𝗲 🔑 𝗖𝗿𝗲𝗱𝗲𝗻𝘁𝗶𝗮𝗹 𝗺𝗶𝘀𝘂𝘀𝗲 🔗 𝗨𝗻𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗲𝗱 𝘁𝗼𝗼𝗹-𝗰𝗮𝗹𝗹 𝗰𝗵𝗮𝗶𝗻𝗶𝗻𝗴 🔍 𝗡𝗼 𝗳𝗼𝗿𝗲𝗻𝘀𝗶𝗰 𝘁𝗿𝗮𝗶𝗹 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝘁𝗿𝘆 𝘁𝗼 𝗿𝗲𝗰𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱 𝗮𝗳𝘁𝗲𝗿 𝘁𝗵𝗲 𝗳𝗮𝗰𝘁 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝘁𝗵𝗲 𝘁𝗲𝗿𝗿𝗮𝗶𝗻 HikmaAI 𝗴𝗼𝘃𝗲𝗿𝗻𝘀. We observe every agent-to-tool interaction as it happens, enforce credential scope and sandbox boundaries in real time, and generate audit-grade evidence automatically — so "what happened?" has an answer before day three, not after. Roman Yampolskiy, AI safety researcher at the University of Louisville, says this highlights how powerful models "can discover and exploit vulnerabilities in ways that were not explicitly anticipated by their developers." Agentic AI incidents are not hypothetical anymore. The question is whether your runtime has an observer in the gap. Curious how HikmaAI governs agent-to-tool actions in real time? DM me for more info! Link in comments.

𝗬𝗼𝘂𝗿 𝗰𝗼𝗱𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁 𝗷𝘂𝘀𝘁 𝘂𝗽𝗹𝗼𝗮𝗱𝗲𝗱 𝘆𝗼𝘂𝗿 𝗲𝗻𝘁𝗶𝗿𝗲 𝗰𝗼𝗱𝗲𝗯𝗮𝘀𝗲. This week a researcher published wire-level evidence that 𝘅𝗔𝗜'𝘀 𝗚𝗿𝗼𝗸 𝗕𝘂𝗶𝗹𝗱 𝗖𝗟𝗜 𝘄𝗮𝘀 𝘂𝗽𝗹𝗼𝗮𝗱𝗶𝗻𝗴 𝗳𝘂𝗹𝗹 𝗚𝗶𝘁 𝗿𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝗶𝗲𝘀 to a company-controlled cloud bucket. One test: 12GB repository. 5.1GB uploaded. The task needed 192KB. In that data: credentials, API keys, full Git history. The fix was a silent server-side flag. Then a public promise that everything will be deleted. 𝗔 𝗽𝗿𝗼𝗺𝗶𝘀𝗲 𝗻𝗼𝗯𝗼𝗱𝘆 𝗰𝗮𝗻 𝗮𝘂𝗱𝗶𝘁. This was not an attack. It was a tool doing what it was built to do, with nobody watching what left the machine. You do not control exports with a policy document; you control them at customs. Egress is where you check the bag. 𝗧𝗵𝗮𝘁 𝗶𝘀 𝘄𝗵𝗮𝘁 HikmaAI 𝗱𝗼𝗲𝘀, 𝗮𝘁 𝘁𝗵𝗲 𝗯𝗼𝘂𝗻𝗱𝗮𝗿𝘆, 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮 𝘀𝗶𝗻𝗴𝗹𝗲 𝗯𝘆𝘁𝗲 𝗹𝗲𝗮𝘃𝗲𝘀. 𝗣𝗿𝗼𝗺𝗶𝘀𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲. 𝗣𝗿𝗼𝘃𝗲𝗻, 𝗻𝗼𝘁 𝗽𝗿𝗼𝗺𝗶𝘀𝗲𝗱. What do you think — should enterprises trust these tools with their codebase? 👇

You added a coding agent. You're faster now. But look down. You're still in the traces — hand on the keyboard, correcting it, re-prompting it, cleaning up after it. You made yourself a faster laborer. That's not the thing. A workhorse left loose in a field is still strong. And completely useless. You don't make it useful by grabbing a rope and pulling next to it. You put it in a harness. A good harness doesn't add horsepower. It channels it. And it does one more thing: it moves you out of the traces and up onto the seat. You stop pulling. You start driving. Here's the reframe: for the last few years the craft was context engineering — feeding the model the right information so it did a good job on the next task. Useful. But it keeps you next to the horse, handing it things. The craft now is harness engineering. Not "how do I get the agent to write this." How do I build the thing that lets the agent write it, prove it's right, and keep me off the keyboard entirely. Three things remain ours: plan, steer, validate. Everything else is down in the harness. I wrote up how we built this at HikmaAI — what broke, what the team resisted, and the one rule that changed how we work more than any model upgrade did. Full post in the comments. #AgenticAI #HarnessEngineering #AIEngineering #Startup #HikmaAI

𝗔𝗹𝗲𝘅 𝗞𝗮𝗿𝗽 𝗷𝘂𝘀𝘁 𝘀𝗮𝗶𝗱 𝘁𝗵𝗲 𝗾𝘂𝗶𝗲𝘁 𝗽𝗮𝗿𝘁 𝗼𝘂𝘁 𝗹𝗼𝘂𝗱. On CNBC this week, the Palantir Technologies CEO went after the closed AI model business, saying "something has gone completely wrong." His argument: enterprises are burning budget on tokens with little to show for it, and worse, they're handing their most sensitive operational data to labs they don't control. His words: CEOs are afraid they'll "waste my time on tokens" while the labs "get my IP." Technical buyers, he said, want control over their compute, their models, their data stack, and their alpha. They want to own the means of production. Strip away the token complaint and there's a much bigger point underneath it: if your data, your prompts, and your IP are leaving your walls to reach a model, you no longer fully own them. Karp keeps landing on the same word — control — and the only architecture that actually delivers it is self-hosted. 𝗧𝗵𝗮𝘁'𝘀 𝗻𝗼𝘁 𝗮 𝗣𝗮𝗹𝗮𝗻𝘁𝗶𝗿 𝘁𝗮𝗹𝗸𝗶𝗻𝗴 𝗽𝗼𝗶𝗻𝘁. 𝗧𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗲𝘅𝗮𝗰𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝘄𝗲 𝗯𝘂𝗶𝗹𝘁 HikmaAI 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 — 𝗮𝗻𝗱 𝘄𝗲 𝗮𝗴𝗿𝗲𝗲 𝘄𝗶𝘁𝗵 𝗵𝗶𝗺 𝗼𝗻 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀. HikmaAI is self-hosted, full stop. We deploy inside your infrastructure — your hardware or your private cloud — not ours. Your logs, prompts, and customer data never leave your perimeter, never transit a third-party API, and are never used to train anything outside your walls. You own the data. You own the IP. You own the compute it runs on. Every enterprise racing to deploy autonomous agents is facing the same trust gap Karp described — except it doesn't stop at the model. It's the agents making tool calls, touching customer data, and executing actions with nobody watching. You can pick whichever model you like, but if the enforcement layer watching your agents isn't inside your own perimeter too, you still haven't solved the problem — you've just moved it. Self-hosting the model without self-hosting the security around it is half a fix. That's why HikmaAI's Intelligent Gateway lives on-premise with you. We don't ask your agents nicely to behave — we sit at the network boundary, inside your infrastructure, and enforce it in real time. No SDK inside your agents. No data sent out to prove it worked. Karp is right that the industry has a control problem. We just think the fix isn't a different model — it's refusing to let your data, your IP, or your security controls leave your building in the first place. Sovereignty isn't a model choice. It's a self-hosted architecture choice, top to bottom. Link to article in comments 👇🏼. #AIsecurity #AIsovereignty #AgenticAI #EnterpriseAI #HikmaAI

HikmaAI turns ONE today! 🎂 One year ago we were an idea. Today we're a product, a team, and a mission that's just getting started. Read what our CEO Nibras Stiebar-Bang has to say about year one — and what comes next 👇

𝗬𝗼𝘂𝗿 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝗺𝗮𝗸𝗶𝗻𝗴 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁𝘀. 𝗡𝗼𝗯𝗼𝗱𝘆 𝗶𝘀 𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝘁𝗵𝗲𝗺. A BMW dealership in Canada deployed an AI chatbot to handle car sales. A customer asked about selling his X3 back. The bot — called "Quinn" — came back with an offer of $27,162. 𝗡𝗼 𝗵𝘂𝗺𝗮𝗻 𝗿𝗲𝘃𝗶𝗲𝘄𝗲𝗱 𝗶𝘁. 𝗡𝗼 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹 𝘀𝘁𝗼𝗽𝗽𝗲𝗱 𝗶𝘁. 𝗡𝗼 𝘀𝗽𝗲𝗻𝗱 𝗹𝗶𝗺𝗶𝘁 𝗲𝘅𝗶𝘀𝘁𝗲𝗱. The number was wrong. It was the customer's loan balance, not the car's market value. The dealer tried to back out. The customer pushed back. 𝗧𝗵𝗲 𝗱𝗲𝗮𝗹𝗲𝗿 𝗵𝗮𝗱 𝘁𝗼 𝗵𝗼𝗻𝗼𝘂𝗿 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗺𝗼𝘂𝗻𝘁 — $𝟱,𝟬𝟬𝟬 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘁𝗵𝗲 𝗰𝗮𝗿 𝘄𝗮𝘀 𝘄𝗼𝗿𝘁𝗵. A car deal today. A contract tomorrow. A compliance breach next week. Agents don't know where the line is unless you draw it for them. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 HikmaAI 𝘄𝗮𝘀 𝗯𝘂𝗶𝗹𝘁 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 — a real-time security layer that sits between your AI agents and the actions they're allowed to take. Before the commitment. Before the damage. Before the invoice. 𝗔𝗜 𝘆𝗼𝘂 𝗰𝗮𝗻 𝘁𝗿𝘂𝘀𝘁. 𝗣𝗿𝗼𝘃𝗲𝗻, 𝗻𝗼𝘁 𝗽𝗿𝗼𝗺𝗶𝘀𝗲𝗱. 🔗 Full story: https://lnkd.in/eBbY3Weq #AgenticAI #AISecurity #AIRisk #EnterpriseAI #HikmaAI

𝗬𝗼𝘂𝗿 𝗮𝗴𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻. 𝗪𝗵𝗼'𝘀 𝘄𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗱𝗼? 🚨 𝗝𝗼𝗶𝗻 𝗼𝘂𝗿 𝗜𝗻𝘁𝗿𝗼 𝘁𝗼 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗼𝗻𝗹𝗶𝗻𝗲 𝗰𝗮𝗹𝗹 𝗼𝗻 𝗝𝘂𝗻𝗲 𝟮𝟯𝗿𝗱, 𝗹𝗶𝗻𝗸 𝗯𝗲𝗹𝗼𝘄 👇🏼. Private inference solves one half of the problem: your data stays inside your environment, nothing leaves your perimeter. But once an agent starts executing autonomously, the open question is what it does with that data — and whether anything steps in when it goes wrong. 𝗧𝗵𝗮𝘁'𝘀 𝘄𝗵𝗮𝘁 XFERENCE 𝗮𝗻𝗱 HikmaAI 𝘀𝗲𝘁 𝗼𝘂𝘁 𝘁𝗼 𝗮𝗻𝘀𝘄𝗲𝗿 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. Xference gives enterprises private, sovereign AI inference. HikmaAI's intelligence is now integrated into that inference layer — detecting risky agent behaviour in real time as it runs, and correcting it at runtime, inside the execution environment rather than after the fact. The result: private inference with agentic security built into the platform. Detection and correction where the agent actually executes, not bolted on downstream. Nibras Stiebar-Bang and Mauro Medda from HikmaAI are joining Andrea Pili the Xference team for a joint briefing on what this means in practice: → Why private inference alone isn't enough once agents start acting autonomously → What it looks like when detection and correction live inside the inference layer → The threat patterns we're seeing in regulated enterprise environments → What you should be asking before your next agent goes into production 𝗧𝗵𝗶𝘀 𝘀𝗲𝘀𝘀𝗶𝗼𝗻 𝗶𝘀 𝗳𝗼𝗿 𝗖𝗜𝗦𝗢𝘀, 𝗖𝗧𝗢𝘀, 𝗮𝗻𝗱 𝗮𝗻𝘆𝗼𝗻𝗲 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗳𝗼𝗿 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘁𝗼𝘂𝗰𝗵 𝗿𝗲𝗮𝗹 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀. No fluff. Just what you need to get your agents under control. 🔗 Register via Luma - https://luma.com/xc9tay6n #AgenticSecurity #PrivateInference #AIGovernance #CISO #CTO #HikmaAI #Xference

𝗧𝗵𝗲 𝗘𝗨 𝗔𝗜 𝗔𝗰𝘁 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗱𝗲𝗮𝗱𝗹𝗶𝗻𝗲 𝗶𝘀 𝗔𝘂𝗴𝘂𝘀𝘁 𝟮, 𝟮𝟬𝟮𝟲. Most teams have started the policy work. Few have built the operational infrastructure to back it up. We've mapped HikmaAI's three-layer platform — Observe, Control, Govern — directly to what the Act requires. Here's the short version: 👁 𝗢𝗕𝗦𝗘𝗥𝗩𝗘 𝗰𝗼𝘃𝗲𝗿𝘀 𝗔𝗿𝘁. 𝟭𝟮 + 𝟭𝟯 Audit logs, full agent visibility, HikmaScore™ per agent — the evidence trail regulators are looking for. 🛡 𝗖𝗢𝗡𝗧𝗥𝗢𝗟 𝗰𝗼𝘃𝗲𝗿𝘀 𝗔𝗿𝘁. 𝟵 + 𝟭𝟰 + 𝟭𝟱 Real-time gateway blocking threats in under 30ms, circuit breaker for human override, adaptive red-teaming that finds vulnerabilities before attackers do. ⚖️ 𝗚𝗢𝗩𝗘𝗥𝗡 𝗰𝗼𝘃𝗲𝗿𝘀 𝗔𝗿𝘁. 𝟵 + 𝟭𝟰 + 𝟳𝟮 Per-agent policy engine, cryptographic attestation chain, and board-ready EU AI Act evidence packages — native, not bolted on. And the one thing most platforms don't mention: HikmaAI deploys inside your own infrastructure. Self-hosted. Air-gapped if needed. Your agent traffic never touches our servers. That removes the DPO conversation entirely. Full blog with the article-by-article crosswalk 👇 https://lnkd.in/dr8NdsqD #EUAIAct #AICompliance #AIGovernance #AIAgents #HikmaAI #DataSovereignt

Very excited about this partnership that we have with The Italian Institute of Artificial Intelligence (AI4I) !!

Following AI Week in Milano, one clear trend stood out above everything else: the definition of enterprise infrastructure risk has fundamentally changed. In the past, moving to the cloud meant handing over computational power and storage. Today, adopting autonomous AI means trusting external systems with your company's actual reasoning, decision-making, and core intelligence. Enterprises now understand the massive leap from conversational AI like Chats to autonomous Agents. When AI reasoning drives real-time actions and tool calls, the security risks multiply. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗱𝗿𝗶𝘃𝗶𝗻𝗴 𝗮𝗻 𝘂𝗿𝗴𝗲𝗻𝘁 𝗱𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿 𝘁𝗿𝘂𝗲 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗦𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆: 𝗼𝗻-𝗽𝗿𝗲𝗺𝗶𝘀𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝘀𝗲𝗰𝘂𝗿𝗲 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗹𝗼𝗼𝗽 𝘀𝘁𝗿𝗶𝗰𝘁𝗹𝘆 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗰𝗼𝗿𝗽𝗼𝗿𝗮𝘁𝗲 𝗽𝗲𝗿𝗶𝗺𝗲𝘁𝗲𝗿. This is exactly why we built HikmaAI. 𝗢𝘂𝗿 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 𝗮𝗻𝘀𝘄𝗲𝗿𝘀 𝘁𝗵𝗲 𝘁𝗵𝗿𝗲𝗲 𝗺𝗼𝘀𝘁 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗯𝗼𝗮𝗿𝗱𝗿𝗼𝗼𝗺 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜: 𝗢𝗯𝘀𝗲𝗿𝘃𝗲: Do you actually know every AI system running in your organization right now? 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: What happens when an autonomous agent goes out of bounds or gets manipulated via a tool call? 𝗚𝗼𝘃𝗲𝗿𝗻: How are you proving continuous compliance (EU AI Act, ISO 42001, NIS2) across your entire agentic footprint? 𝗔𝘀 𝘁𝗵𝗲 𝘂𝗻𝗶𝗾𝘂𝗲 𝘀𝗲𝗹𝗳-𝗵𝗼𝘀𝘁𝗲𝗱 𝗮𝗻𝗱 𝗼𝗻-𝗽𝗿𝗲𝗺𝗶𝘀𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗶𝘀 𝘀𝗽𝗮𝗰𝗲, HikmaAI gives CISOs and technology leaders the power to Observe, Control, and Govern every AI interaction through an API-first architecture—without ever relying on cloud dependencies, exposing sensitive data, or sacrificing execution speed. 𝗜𝗳 𝘆𝗼𝘂 𝗮𝗿𝗲 𝗿𝗲𝗮𝗱𝘆 𝘁𝗼 𝘀𝘁𝗼𝗽 𝗵𝗼𝗽𝗶𝗻𝗴 𝗳𝗼𝗿 𝗔𝗜 𝘀𝗮𝗳𝗲𝘁𝘆 𝗮𝗻𝗱 𝘀𝘁𝗮𝗿𝘁 𝗽𝗿𝗼𝘃𝗶𝗻𝗴 𝗿𝘂𝗻𝘁𝗶𝗺𝗲 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗼𝗻 𝘆𝗼𝘂𝗿 𝗼𝘄𝗻 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗹𝗲𝘁’𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁. 👉 Learn more or request a threat model demo at: https://hikmaai.io/ #AIWeek #Milano #DigitalSovereignty #AgenticSecurity #Cybersecurity #EnterpriseAI #HikmaAI