The "factory of the future" is no longer just a vision – it’s here. Leading manufacturers are already using Digital Twins to optimize operations, predict maintenance, and adapt to market shifts in real time. But scaling AI in manufacturing isn’t just about adopting new technology. It requires a data architecture that eliminates silos and enables true enterprise AI. @McKinsey puts it bluntly in “Digital Twins: The Next Frontier of Factory Optimization": 💡 "Digital twins are set to evolve from a nice-to-have technology into a must-have tool for manufacturers of all kinds." ⚡ But here’s the challenge: fragmented data models and architecture slow down AI adoption. ⚡ And this prevents companies from making the leap from isolated proofs-of-concept to fully operational AI systems. This is where RelationalAI comes in. 💡 As a @SnowflakeDB native application, we help manufacturers integrate siloed data and unlock AI-powered knowledge graphs - capturing the complex relationships between physical assets, processes, and business goals while your data remains secure within Snowflake. The result: 💡 Faster, more accurate decision-making 💡 Optimized factory operations 💡 AI-Driven insights at scale Want to learn how leading manufacturers are implementing Digital Twins? Check out the full McKinsey article in the comments. Or connect with us to discuss how RelationalAI can accelerate your enterprise AI journey without complex data migrations or security compromises.

What if you could replace 205,000 lines of code with just 10,000 AI-powered rules? That’s exactly what @BlueYonder did with RelationalAI in @SnowflakeDB. On last week’s Q4 earnings call, Snowflake CEO @RamaswmySridhar shared that Blue Yonder “processes over 20 billion AI predictions daily” providing "powerful supply chain intelligence," something that's become even more critical as global trade evolves. But most people don’t realize that relational knowledge graphs inside Snowflake, powered by RelationalAI, are helping Blue Yonder get to the next level in their AI journey. At Snowflake BUILD, RelationalAI’s Founder and CEO @molhamaref and VP of Applied Research Jay Yu illustrated how leading companies are building intelligent applications, highlighting the Blue Yonder case study. 1️⃣ 205,000 lines of business logic reduced to 10,000 rules & SQL statements. Instead of tangled, hard-to-maintain code, Blue Yonder modernized its infrastructure, creating a new intelligent app platform using RelationalAI. 2️⃣ Everything stays inside Snowflake. With RelationalAI running on Snowpark Container Services, both data and logic stay native—eliminating unnecessary complexity. 3️⃣ Goodbye, soul-crushing complexity. No more convoluted applications that are painful to build and maintain. RelationalAI makes mission-critical applications dramatically simpler and more powerful. Hello, intelligent knowledge graph layer supporting many more AI workloads including graph analytics / insights, math optimization, GNN and GenAI. All on RelationalAI technology inside Snowflake. Want to learn more? Watch the 8 minute fireside chat with Jay Yu below. Want to see it in action? Watch the full 28-minute talk, with Molham and Jay.