Strategy

🔍 Why don't your metrics ever match? Three dashboards. Three different revenue numbers. The problem usually isn't your BI tool. It's the missing semantic layer underneath it. Our new Semantic Layer Foundations course explains one of the most important pieces of modern data infrastructure and why it matters even more in the age of AI. In just over an hour, you'll learn: 🔹 Why metrics differ across dashboards 🔹 What a semantic layer actually is 🔹 How governed business definitions create a single source of truth for BI and AI As AI agents begin querying and analyzing enterprise data, consistent business context isn't optional. It's what keeps AI insights accurate, governed, and trustworthy. The course is free and self-paced. 👉 Register here: https://ow.ly/o1qJ50ZuUZJ #SemanticLayer #EnterpriseAI #DataStrategy #BusinessIntelligence #StrategyMosaic

Everyone is talking about AI models. But can you trust their answers? Without governed business context, AI can be expensive, inconsistent, and difficult to trust. A recent benchmark found that combining AI with a governed semantic layer can: 🔹 Improve answer accuracy 🔹 Reduce AI token costs by up to 50% 🔹 Cut AI agent usage by up to 98% As enterprises scale AI, trust, governance, and cost efficiency are becoming as important as model performance. Discover how governed AI analytics can improve accuracy while reducing costs: https://ow.ly/arGO50ZuUWE #AI #DataAnalytics #BusinessIntelligence #DataGovernance #EnterpriseAI

AI doesn't have a data problem. It has a context problem. Enterprise AI can access your warehouse, but without governed business definitions, it doesn't know what your metrics, entities, or rules actually mean. That's why two AI agents can answer the same question differently. Join our live demo led by Johannes Silhan to see how Strategy Mosaic gives AI the semantic foundation it needs to reason consistently. In this session, we'll show you how to: ✔ Build a semantic model visually in Mosaic Studio, with no SQL required ✔ Connect an AI agent using MCP ✔ Compare responses from raw schema versus a governed semantic model ✔ Deliver consistent answers across AI agents, dashboards, and analytics Whether you're building AI applications, managing enterprise data, or evaluating semantic layers, you'll leave with a practical understanding of how governed business context improves AI accuracy. 📅 Thursday, August 6, 2026 🕙 10:00 AM BST / 11:00 AM CEST Save your spot: https://ow.ly/KWi850ZqM2j #EnterpriseAI #SemanticLayer #AgenticAI #DataGovernance #StrategyMosaic

AI is only as powerful as the data foundation behind it. Franklin Templeton's AI journey didn't start with a new model. It started with a unified, governed data foundation. Following the acquisition of Putnam Investments, Franklin Templeton consolidated three separate analytics environments into a single Strategy-powered platform, creating consistent business logic, stronger governance, and a scalable foundation for AI. The result: 🔹 Unified analytics across the organization 🔹 Enterprise-grade governance and data consistency 🔹 AI-powered dashboards, natural language querying, and self-service analytics 🔹 Faster, more informed decision-making at scale As AI adoption accelerates, trusted data and governed business context become the foundation for delivering reliable insights. Read the full customer story: https://ow.ly/jYTC50Zu5N9 #CustomerStory #EnterpriseAI #DataGovernance #SemanticLayer #StrategyMosaic

Thank you to everyone who joined us at The Library at Lloyd's of London for AI: Myth or Reality – Strategic Perspectives in Insurance. Alongside, Affinity Initiative, we brought together independent experts and practitioners for honest, practical conversations on where AI genuinely creates value in insurance and where it introduces new risk. A huge thank you to our brilliant speakers for sharing their insights: 🔹 Adi Hazan. AI Internals: Understanding AI from the inside so you can prepare for cyber attacks 🔹 Antony Elliott – AI, Energy, and the Future of Insurance: Navigating Europe's Challenges to Unlock AI's Next Competitive Edge Great discussions, sharp questions, and a room full of people willing to cut through the hype. Thank you to everyone who made it such a valuable afternoon! A special thank you to Nicolas Babin who unfortunately was unable to deliver his session due to unforeseen circumstances. We look forward to welcoming him back at a future event. #Insurance #ArtificialIntelligence #CyberRisk #DataGovernance #LloydsOfLondon #Insurtech #RiskManagement

Join François Dupont for a live webinar exploring how AI agents can move beyond chat interfaces to interact with enterprise systems, trigger workflows, and deliver real business outcomes, all while operating within a governed framework. In this session, you'll see: → A real-world AI agent scenario in action → How MCP connects agents to enterprise tools and data sources → Why a semantic layer is essential for trusted, consistent AI outcomes → How Mosaic provides governed business context across every model and use case → Practical strategies for moving from AI experimentation to enterprise-scale deployment As organizations race to adopt AI agents, the challenge isn't building them. It's giving them the context, governance, and connectivity they need to create value safely and reliably. See what's possible when AI agents are connected to the right foundation, register now: https://ow.ly/h6nx50ZcLRo #AIAgents #EnterpriseAI #MCP #SemanticLayer #StrategyMosaic

Benchmarks such as Spider and PICARD show 70–80% text-to-SQL accuracy. That sounds impressive until you realize it means your AI is wrong on up to 30% of data queries, and often doesn’t know it. The fix isn’t better prompting. It’s better architecture. When an LLM generates SQL by guessing at raw schemas, errors are inevitable. When it generates SQL from a governed semantic layer, where joins, metrics, and business logic are already encoded, accuracy stops being a gamble. Forrester lays out exactly why that distinction matters. Read the full report, Make Data AI Ready Via Semantic Layer Platforms, courtesy of Strategy: https://ow.ly/PyV450ZqMbh #EnterpriseAI #SemanticLayer #DataGovernance #AgenticAI #AIArchitecture

For Honeywell Technologies, supporting mission-critical manufacturing meant making trusted data consistent, scalable, and available across thousands of users. By modernizing its analytics architecture with Strategy Mosaic, Honeywell unified 20 data pipelines, standardized business definitions, and delivered governed data to engineers and analysts through the tools they already use. The results included: → Unified 20 data pipelines into a governed semantic layer → Reduced strain on operational systems by moving reporting to a governed analytical store → Delivered consistent, trusted data across 20+ federal agencies and 7,000 end users → Achieved millions of dollars in savings while creating an AI-ready analytics foundation With governed data powering reports, applications, and APIs, Honeywell teams spend less time reconciling data and more time delivering mission-critical outcomes. As Samuel Feinberg, Manager, Data Analytics Platform at Honeywell FM&T, puts it: "We save millions of dollars, implementing an affordably priced data connector, and other elements of the Strategy ecosystem." Read the full customer story here: https://ow.ly/1t0w50ZowV9 #CustomerStory #DataGovernance #EnterpriseAI #DataAnalytics #StrategyMosaic

Your AI is only as trustworthy as the data model behind it. If metrics aren't governed, neither are your AI answers. Join our hands-on workshop to see how Mosaic Studio helps you build a governed semantic model that both people and AI agents can trust without writing a single line of code. You'll see how to: 🔹 Build a semantic model from multiple data sources in minutes 🔹 Use AI to speed up data preparation, metric creation, and hierarchy modeling 🔹 Apply governance and security that travel with every query 🔹 Connect governed metrics to BI tools and AI agents through MCP 🔹 Deliver consistent answers across dashboards, reports, and AI Whether you're preparing your data for analytics, copilots, or autonomous agents, this session shows how to build a trusted foundation that scales. 📅 July 24 at 12:00 PM EST 📅 July 28 at 10:00 AM BST / 11:00 AM CEST Register here: https://ow.ly/SR1650ZowRu #EnterpriseAI #SemanticLayer #DataGovernance #AIAgents #StrategyMosaic

AI agents can query your data. That doesn't mean they understand your business. Ask an AI agent about ARR, your top customers, or revenue, and the answer often depends on how it interprets your data. Without governed business context, even the most capable models are forced to guess. Join our live demo led by Johannes Silhan to see how Strategy Mosaic gives AI a semantic foundation, so every agent, dashboard, and application works from the same trusted business definitions. In this session, you'll see: • How to build a semantic model visually in Mosaic Studio, with no SQL required • The difference between AI working from raw schema versus governed business context • How MCP connects AI agents to trusted enterprise knowledge for consistent answers Whether you're an analyst, data engineer, or AI practitioner, you'll leave with a practical understanding of what it takes to make AI reliable on enterprise data. 📅 Thursday, August 6, 2026 🕙 10:00 AM BST / 11:00 AM CEST Register here: https://ow.ly/m3tn50ZqLpB #EnterpriseAI #SemanticLayer #AgenticAI #DataGovernance #MCP