RelationalAI Recognized as a One to Watch in Snowflake's Modern Marketing Data Stack Report image

RelationalAI Recognized as a One to Watch in Snowflake's Modern Marketing Data Stack Report

RelationalAI enables joint customers to build intelligent solutions on Snowflake's Data Cloud and make better business decisions.

Introducing the Industry’s First AI Coprocessor for the Data Cloud image

Introducing the Industry’s First AI Coprocessor for the Data Cloud

As an AI coprocessor, RelationalAI extends your data cloud to support graph analytics, reasoning, optimization and other composite AI workloads. You can access RelationalAI directly from Snowflake. Snowpark Container Services (private preview) enables you to execute RelationalAI’s engine entirely within your Snowflake account.

Press Release: RelationalAI Unveils the AI Coprocessor and Runs Securely in the Snowflake Data Cloud with New Snowpark Container Services image

Press Release: RelationalAI Unveils the AI Coprocessor and Runs Securely in the Snowflake Data Cloud with New Snowpark Container Services

RelationalAI Brings Knowledge Graphs and Composite AI to the Snowflake Data Cloud and Language Models.

Using Rel for Machine Learning Data Preprocessing image

Using Rel for Machine Learning Data Preprocessing

RelationalAI's declarative modeling language Rel can be a powerful tool for machine learning data preprocessing. It is concise, readable, and facilitates testing and debugging in development. Rel can significantly simplify your machine learning data pipeline.

RelationalAI at the Knowledge Graph Conference image

RelationalAI at the Knowledge Graph Conference

We are delighted to be attending and sponsoring the Knowledge Graph Conference again this year. Last year was an incredible event and this year is lining up to be just as exciting! Our VP of Strategic Development, Aisha Quaintance, is chairing the first ever Semantic Layer track. We are also presenting a masterclass and hands-on workshop, taking part in a fireside chat with Snowflake discussing financial services, and co-hosting a happy hour with Women in Data.

Hybrid and Content-based Recommender Systems in Rel - Part 3 image

Hybrid and Content-based Recommender Systems in Rel - Part 3

In this series of blog posts, we show how to implement neighborhood-based, graph-based, content-based, and hybrid recommender systems using RelationalAI’s declarative modeling language, Rel. The implementations of these algorithms demonstrate the efficiency of our Relational Knowledge Graph System (RKGS) for aggregating over paths on large and sparse graphs, computing similarities using our graph analytics library, and building compact, easy to read models, without needing to transfer data outside of our system.