Cloud-centric AI cannot always keep up with the need for instant decisions and strict security. More and more enterprises are turning to AI inference at the edge, bringing processing closer to the source for faster, smarter outcomes. In our latest blog, we explore how edge inference is reshaping enterprise AI and what it takes to build secure, scalable infrastructure. What you will learn: • How edge inference reduces latency with real-time, on-device processing • Why enterprises adopt it to cut cloud costs and meet compliance needs • Key factors for choosing the right platform • How Mirantis’ Kubernetes-native, composable solution streamlines edge inference without sacrificing control or flexibility Read the full guide: https://buff.ly/Rzcmmqj

🚀 Meet Airia’s Enterprise AI Orchestration Platform AI agents are the future — but scaling them in enterprises is hard. Airia makes it simple. ✨ What you get with Airia: ⚡ No-Code Agent Builder — build agents 70% faster 🔗 Pre-Built Data Connectors — reduce integration costs by 50% 🤖 Intelligent AI Operations — cut operational expenses by 30% 🔒 Enterprise-Grade Security — HIPAA, SOC2, and advanced encryption ☁️ Flexible Deployment — cloud, private cloud, or on-premises 🧠 Model Agnostic — use any AI model, no vendor lock-in 🌍 Unified AI Platform — streamline operations across industries 💡 Dedicated Support — 95% customer satisfaction 👉 Check out more here: https://lnkd.in/eYntDqj3 #AI #EnterpriseAI #NoCode #DigitalTransformation #Innovation #Airia

AI isn’t one-size-fits-all. Some workloads need the agility of cloud. Others demand the security and control of private or on-premises environments. That’s where hybrid AI comes in. For mid-market enterprises, the challenge is balancing innovation with governance: • Running AI where it performs best—cloud, on-premises, or both • Protecting sensitive data while enabling faster insights • Enforcing compliance and lifecycle controls across environments Ntirety helps organizations build AI-ready, hybrid foundations that deliver performance without compromise. Hybrid AI isn’t a trend. It’s how mid-market companies balance agility with regulatory pressure. Make hybrid AI your advantage. https://lnkd.in/eZEpH6xn #HybridAI #AIReadiness #AICompliance #Ntirety #FutureReady #MidMarket

🔐🤖 Supporting government agencies with secure and effective AI is a significant priority for us. With Gemini for Government, we’re bringing together our FedRAMP High–authorized cloud, Gemini models, and agentic solutions into a single platform designed for the public sector in the US 🇺🇸. From enterprise search to NotebookLM, from pre-built AI agents to image and video generation, the package equips agencies with the tools they need to modernize workflows and serve citizens more efficiently. Security is built in at every layer, while transparent pricing and flexible deployment make it easy to adopt and scale. This is about giving government teams the same innovation and resilience that organizations around the world already trust, adapted to the unique needs of the #publicsector. https://ow.ly/LQ3F50X29iF

Generative AI is moving beyond marketing and creativity- it’s now 𝐫𝐞𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬. When integrated with Cloud workflows, GenAI can: ⚡ Predict infrastructure demand and auto-scale resources ⚡ Spot anomalies and prevent downtime before it happens ⚡ Optimize performance and cost dynamically For enterprises, this means less firefighting and more foresight. At Northcorp, we’re deploying AI + Cloud solutions that give decision-makers visibility, agility, and confidence. 👉 Would you trust AI to manage critical infrastructure decisions for your enterprise?

When cloud first emerged, adoption hinged on one big unlock: SSO. It was the trust layer that made the cloud usable at scale. AI needs not one, but three equivalent layers to truly work in the enterprise: 1️⃣ Trust & Guardrails — policy and governance to keep outputs safe. 2️⃣ Contextual Knowledge — grounding in the company’s own data so answers are relevant. 3️⃣ Audit & Attribution — visibility into why the AI responded the way it did. Without these layers, AI feels risky. With them, it becomes transformative. Do the AI tools you're using at work (or at home!) have all 3 of these layers?

AI tools are often built for a cloud setting. But moving all your data to where that AI system exists isn’t always possible, especially when integrated into highly regulated industries. @Cloudera brings AI to data anywhere, so you get smarter insights without changing how you work or putting your security at risk. This marks a new era in AI where intelligence adapts to your environment, not the other way around. Learn more: http://bit.ly/47Xqwn9    #DataSecurity #DataPrivacy #EnterpriseAI

Ten years ago, every enterprise was asking the same question. “How do we move to the cloud?” Today, the question is shifting. “How do we manage AI agents?” Just like cloud transformed infrastructure... Agent orchestration will transform how work gets done. In the near future, enterprises won’t rely on one big AI model. They’ll run fleets of specialized agents, each focused on a specific task. The real advantage will come from managing how those agents work together: → Coordinating decisions across departments → Sharing insights instantly between systems → Preventing conflicts before they happen → Automating execution end to end The companies that master this will move faster than their competitors. They’ll adapt quicker. They’ll scale without adding headcount. Cloud was the last big operational shift. Agent orchestration is the next one. P.S. What are your thoughts on agent orchestration?