Knowledge graphs make LLMs accurate, transparent and explainable. Netflix uses knowledge graphs for personalized movie recommendations; LinkedIn uses it for feed and job search recommendations; financial institutions use knowledge graphs for transaction surveillance, fraud detection and more. Knowledge graphs make the AI systems more reliable and trustworthy. Thanks to RelationalAI, you can run graph algorithms on Snowflake data to build AI apps. ✅ Build a recommender system using RelationalAI’s Snowflake Native App: https://okt.to/tSlIZ6 ✅ Building a customer social graph using RelationalAI: https://okt.to/AOPbFc What are some use-cases? Say you run a restaurant and one of these days, the food was unpleasant and your customers were unhappy. To mitigate the risk of bad word of mouth, you fix the food quality issue and offer your customers a free coupon to compensate. Well, it might be too late since they already ranted about it to their friends or coworkers who also happen to dine at your restaurant. A knowledge graph can help identify the social graph of your customers. Perhaps you can offer a discount code to all the affected customers along with their first degree connections on the social graph as well. How cool!
The diagram showing RelationalAI Knowledge Graph within Snowflake shows the ease with which you can use a Knowledge Graph while also obtaining all the benefits of the Snowflake environment. Great approach
A great use case example.