Enterprise IT vendors are moving to position themselves for the AI era. As subsequent M&A activity picks up, a tendency to bolt together "AI stacks" for IT teams should be challenged. True value from enterprise AI will come from empowering those familiar with the context that makes business processes tick: business users and analysts. In my latest article for @TechRadarPro I discuss how the AI Data Clearinghouse process helps address the root causes of stunted enterprise AI rollouts by empowering businesses to uncover transparent, trusted AI use cases. Read more here: https://lnkd.in/gVqumAfJ
How AI Data Clearinghouse can boost enterprise AI
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Data isn’t just the fuel of AI—it’s the foundation of every breakthrough. But here’s what’s often overlooked: without open semantic interchange (OSI), even quality data remains trapped in silos. OSI enables different systems, formats, and organizations to share and understand data seamlessly, creating the interoperable ecosystem that AI desperately needs to reach its full potential.
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Cloudera expands its Enterprise AI Ecosystem! By partnering with ServiceNow, Fundamental, Pulse, and Galileo.ai, Cloudera now offers end-to-end, production-ready AI solutions that turn enterprise data structured and unstructured into intelligent, governed actions. “The Enterprise AI Ecosystem has become a cornerstone of our strategy to help large enterprises navigate the complexities of AI adoption,” said Abhas Ricky, Chief Strategy Officer at Cloudera. From predictive analytics to AI workflow automation, enterprises can scale AI across operations with confidence, transparency, and compliance. Know how Cloudera is helping companies become truly AI-native:- https://lnkd.in/dCsmUjF2 #Cloudera #EnterpriseAI #AIEcosystem #DataIntelligence #AIWorkflow #MachineLearning #DigitalTransformation #PredictiveAnalytics #AIAtScale #bestplacetowork #ittechpulse
Cloudera Helps Customers Become AI Native with Additions to Enterprise AI Ecosystem ittech-pulse.com To view or add a comment, sign in
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"Enterprises that want to safely and effectively put their business data to work with AI need real-time access combined with semantic understanding. AI needs to comprehend what data means, not just where it lives," said Manish Patel, Chief Product Officer of CData Software. "With Connect #AI, companies can for the first time give AI applications governed, live access to data across hundreds of systems with the contextual intelligence that transforms AI from a productivity experiment into a trusted enterprise tool" #AI #EnterpriseData #DataIntegration #MachineLearning #AIApplications #CData #ConnectAI #DigitalTransformation https://lnkd.in/gGMBvNyz
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Qlik Predict Brings No-Code Predictive Intelligence to the Front Lines of Business Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), has announced the rapid adoption of Qlik Predict, as enterprises turn to real-time, explainable forecasting to drive smarter, faster decisions at scale. Built for enterprise-grade reliability and governance, Qlik Predict transforms how organisations leverage machine learning, putting no-code predictive models directly in the hands of business users across functions. Read More: https://lnkd.in/dZn8i3rG Qlik Brendan Grady #Qlik #PredictiveIntelligence #DataIntergration #DataQuality #Analytics #ArtificialIntelligence #AI #SupplyNetworkAfrica #SNA
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Where 2024 saw a huge emphasis on AI adoption to improve productivity, 2025 is seeing enterprises move on to integration. But as our recent survey reveals, data access remains a big challenge. More in this Forbes article: https://bit.ly/46ver7Q
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The new CData Connect AI links AI assistants, agents and application workflows to more than 300 data sources, providing governed data with semantic-rich context. https://okt.to/LhpmZG
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Every AI model fails when sales and marketing can't agree on what 'customer' means. Fragmented and inconsistent data semantics across platforms are slowing AI adoption and holding back innovation. The Open Semantic Interchange (OSI) initiative – an open-source, vendor-neutral standard for defining and sharing business data semantics tries solving this trillion dollar problem. #DataQuality #Senantics #ArtificialIntelligence #AgenticAI https://lnkd.in/d-7GKHG9
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As Ken highlights here, there's no AI without data, and the most valuable data is likely locked away and significantly difficult to access without highly adaptable integration technology.
Global Software Industry CEO | Investor, Advisor & Growth Strategist | Driving Growth and Market Expansion in Enterprise AI, Data, and SaaS | Turning Collective Intelligence into Business Acceleration
In a recent conversation with a Fortune 100 Bank CIO, they conveyed - We’ve been investing in dis-integrated systems for years - and with AI becoming a business priority, it’s becoming harder to explain why.” I’ve shared some thoughts on why data harmonization is the essential precursor to meaningful AI and CI success—and why the future leaders in the AI race will be those who first master the value of the data they already own… https://lnkd.in/eNbfBdzB
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Cloudera expands its Enterprise #AI Ecosystem with four new partners to enhance predictive modelling, workflow automation, and AI observability for businesses, designed to deliver production-ready artificial intelligence solutions for customers. The new partnerships with ServiceNow, Fundamental, Galileo.ai, and Pulse aim to strengthen Cloudera's AI capabilities and address areas including predictive modelling, workflow automation, document intelligence, and AI observability. https://lnkd.in/gDGBK87R
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Hey everyone! 👋 I’ve been working closely with Abacus.AI, and I’m genuinely impressed with how powerful, practical, and enterprise-ready their platform is for building and deploying AI. If you’re exploring ways to bring AI into your products or workflows—beyond the hype and into real outcomes—this is a platform you should seriously consider. Here’s why Abacus.AI stands out: End-to-end, not just a model It’s a full-stack AI platform: data ingestion, fine-tuning, vector search, agents, guardrails, evaluation, and production deployment. You can go from prototype to production with versioning, monitoring, and governance all built in. State-of-the-art LLM orchestration RouteLLM lets you access many top models behind a single API, optimize cost/latency/quality automatically, and swap models without refactoring. Built-in retrieval (RAG), structured outputs, and evaluation tools make enterprise LLM use cases much easier to ship. Real-time, production-ready AI Low-latency inference, autoscaling, and robust monitoring so your AI features are reliable in production. Strong support for privacy, compliance, and security—critical for regulated industries. Vector DB + Knowledge Hub Bring your data—docs, databases, tickets, logs—and build powerful semantic search + RAG experiences. Document parsing, chunking, embeddings, and guardrails are handled for you. Agents that actually work in enterprise settings Multi-step, tool-using agents that can read from your systems (and with proper permissions, take actions). Clear observability: traces, retries, safety filters, and approval workflows. Practical ML beyond LLMs Forecasting, anomaly detection, personalization, and recommendation systems—battle-tested for real business KPIs. You can combine classical ML with LLMs in a single workflow. What this means in practice: Faster time-to-value: You don’t have to stitch together 10 different tools. Lower risk: Built-in evals, safety, and governance help you move fast without breaking things. Flexibility: Start small with one use case, scale across teams without hitting platform limits. If you’re considering: An AI copilot for internal teams or customers RAG over your proprietary data Automated agents with strong guardrails Recommenders, personalization, or forecasting in production Or just a unified platform to standardize AI across your org Shoot me a message. I’m happy to set up a call and walk you through how Abacus.AI can fit your roadmap. Whether you’re early-stage or at enterprise scale, there’s a clear path to impact. DM me and let’s chat 🤝
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Preparing CROs & CEOs for the future of B2B SaaS | GTMshift | CRO Functional Head @ Pavilion | Former CRO | Co-Founder @ PreSales Collective (Acquired) | Breaking The GTM Playbook |
5dGreat article. The following concept really stood out to me because it’s the best approach to improving accuracy and minimizing risk. I heard about “SLM” last year and that concept really makes a ton of sense. “Connecting AI models directly to vast stores of sensitive data is a governance nightmare for boards wary of risk. A better approach is selective: giving AI access only to the limited, highly relevant data needed for each specific use case.”