Edward Heraux, PMP, MCSE’s Post

How can enterprises maintain brand consistency at scale? The Production Reality Gap whitepaper, created in collaboration with Amazon Web Services (AWS), explores how to build systems that avoid common pitfalls. You’ll discover 👇 ✔️ Why prompting alone as an adjustment to the quality of inference is not enough for an enterprise content workflow ✔️ Which technical metrics actually impact production (like inference speed, reproducibility, and output quality) ✔️ How to add automation and control to visual AI with the right tools and platform ✔️ Ways to build AI pipelines that scale, without adding unnecessary complexity Learn how Fortune 1000 companies are building scalable, reliable systems that deliver real-world results. Download the free whitepaper today ➡ https://go.bria.ai/4ncMJlj #GenerativeAI #AI #AIforBusiness

We’re spending trillions on AI… but most of it isn’t paying off. PYMNTS says global AI spend hit $235 billion last year and could reach $2.8 trillion by 2029. Yet revenue growth? Pretty much flat. That’s the AI ROI problem — huge budgets, tiny impact. If you work in data or analytics, this is where we earn our keep: proving what’s actually working. Are we tracking profit, or just how many models we shipped? Do we know if those automations saved money or just moved the costs around? Can anyone point to a dashboard that shows payback time, not hype? Simple test: - Show me margin change, not model accuracy. - Compare teams with vs. without AI help. - Count the hidden work — training, cleaning, fine-tuning. Until we treat AI like any other investment, it’ll stay a shiny side project with a trillion-dollar tab. What’s one metric you’d use to prove AI’s real value? #AI #BusinessAnalytics #DataStrategy #ROI #Retail #Automation Source: 👉 https://lnkd.in/eqzCqeud

Read to learn how Bria AI and Amazon Web Services (AWS) bridge the GenAI pilot to production gap for enterprise customers

Databricks Partners with OpenAI to Embed GPT-5 for Enterprise AI Solutions Databricks announced integration of OpenAI's GPT-5 and additional models into its platform, including Agent Bricks, streamlining AI application development and deployment for enterprises. Key points include: - Direct access to GPT-5 enhances analytics and personalization. - Enables companies to scale AI-driven customer engagement. - Projected to generate $100 million in revenue for Databricks. This partnership offers enterprises simpler, scalable AI tools, accelerating AI adoption for business intelligence and operational efficiency. Source: https://lnkd.in/dhEVPmWP 👉👉 Follow Us ✨ 🙏 ➡️ Global AI Talks 🌎✨ 📌Country Pages🎯 ➡️ US AI Talks 🇺🇸 ➡️ UK AI Talks 🇬🇧 ➡️ Canada AI Talks 🇨🇦 ➡️ India AI Talks 🇮🇳 #EnterpriseAI #GPT5 #Databricks #AIPartnership #BusinessIntelligence

🚀 The future of decision-making is intelligent. Artificial Intelligence (AI) and Business Intelligence (BI) are converging, transforming how organisations interpret data, forecast change, and act with confidence. Here’s what’s driving this shift:  - BI platforms are rapidly moving to the cloud, enabling real-time, scalable insight.  - AI is enhancing BI with predictive models and natural-language queries that remove traditional data barriers.  - Organisations combining AI + BI are reporting measurable improvements in agility, accuracy, and strategic foresight. Together, AI + BI enable:  Real-time, AI-enhanced dashboards that power faster, smarter action.  Automated anomaly detection and context-aware recommendations.  Embedded analytics that integrate seamlessly into day-to-day workflows.  Responsible, transparent use of AI aligned with emerging governance frameworks. The opportunity is clear: when intelligence becomes integrated, decision-making becomes transformative. Is your organisation ready to unlock the potential of AI + BI? 👇 We’d love to hear how you’re using (or planning to use) AI + BI in your workplace. sen.nz/3x4qm2 #ArtificialIntelligence #BusinessIntelligence #DataDriven #AIinBI #DigitalTransformation #Innovation #Leadership #SmartDecisions 

🤖 The real power of AI isn’t just in training models — it’s in making them work for people. Over the past few years, I’ve gone from building ML models that predict outcomes to designing AI systems that understand context. At Tri Counties Bank, I’ve been fine-tuning GPT-3.5 and LLaMA-2 models, integrating them with Retrieval-Augmented Generation (RAG) pipelines and scalable APIs on Azure. These systems don’t just answer questions — they reason, adapt, and learn from data in real-time. Before that, at Omnicell, I engineered production-grade ML pipelines on AWS SageMaker, automated data workflows, and deployed low-latency inference APIs that powered decisions at scale. What drives me every day? 👉 Turning AI from a technology into a teammate. 👉 Building pipelines that can think, not just predict. 👉 Scaling GenAI with MLOps so innovation doesn’t stop at deployment. We’re entering an era where AI won’t replace humans — it’ll amplify them. And I’m all in for building that future. 618-471-1471 govardhan03ra@gmail.com #AI #MachineLearning #GenerativeAI #LangChain #MLOps #LLM #Innovation

Lineage, Observability, and Trust — The Backbone of Responsible AI In the rush to build GenAI and data-driven platforms, many enterprises overlook one critical foundation — trust in data. True Responsible AI doesn’t start at the model layer. It starts with data lineage — knowing exactly where data came from, how it was transformed, and who used it. Without lineage and observability, AI becomes a black box — impressive in output, but impossible to audit or explain. When you combine lineage (traceability), observability (real-time visibility), and governance (accountability), you don’t just achieve compliance — you build confidence. That’s what enables business users to rely on AI-generated insights and regulators to trust the systems behind them. As enterprises scale LLMs and agentic workflows, platforms like Microsoft Purview, Collibra, and Unity Catalog are no longer optional — they are the new safety rails for data-driven decision making. In AI, transparency isn’t bureaucracy — it’s the currency of trust. #AI #DataGovernance #DataLineage #ResponsibleAI #MicrosoftPurview #Databricks #Azure #Observability #DataTrust

Martech sprawl is like that “perfect on paper” date—best-of-breed tools, microservices, all the right promises. But then a major red flag shows up: it’s sabotaging your AI potential behind your back. 🚩 Check out our recent blog on why a fragmented stack is problematic for AI: https://ow.ly/rKHm30sQ6Nl

Martech sprawl is like that “perfect on paper” date—best-of-breed tools, microservices, all the right promises. But then a major red flag shows up: it’s sabotaging your AI potential behind your back. 🚩 Check out our recent blog on why a fragmented stack is problematic for AI: https://ow.ly/qyYY30sPWXH