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In 2025, Knowledge Graphs are set to become a critical engine for enterprise AI strategies. Below are four predictions for how the field will evolve—and why the Kobai platform, in partnership with Databricks, offers tangible business benefits for organizations aiming to harness the full power of their data.

Continuous Integration has expanded over the course of my career. Originally, it was mostly only used to refer to the building processes of an application automatically, but now it’s taken on a larger role of generic automations as well as tools like GitHub Actions, Circle CI, Gitlab CI (a group of tools I affectionately call CI providers) become more commonplace.

At Kobai, we’re passionate about helping organizations harness the full potential of knowledge graphs to unlock actionable insights and accelerate decision-making. That’s why we couldn’t be more thrilled to share this insightful article by a long-time friend and industry expert, Doug Kimball .

In this series, we’ll go over how the platform engineering team at Kobai is able to handle cutting edge DevOps implementations like ephemeral environments, manage to wrangle our cloud spending to just a few thousand dollars a month for over 20 environments, and create automated regression testing suites — all while maintaining a lean team.

Earlier this year, Microsoft announced their GraphRAG project, and ignited a storm of interest in how Knowledge Graphs can improve results from Generative AI. In this series, we will take a high level look at the characteristics of several graph-enabled RAG approaches (including Microsoft-style GraphRAG) and compare them to other approaches on a simple use case.

Based on graph technology (Kobai Saturn based on lakehouses), a tool to help find the answer to “so what” in your data. Crunching the data to find an answer is great, but also being able to quickly find root cause analysis or ways to address the issue quickly and confidently, that’s where Kobai really shines.

Kobai Saturn is a recently released RDF graph backend from Kobai. The basic idea behind Kobai is to provide business users and subject matter experts (SMEs) the means to build and interact with knowledge graphs.

The data lakehouse is a hybrid term used to denote some of the structures we would find in a more ordered data warehouse with the expansiveness and lower cost functionality of the data lake. But, finding our way around the data lakehouse, even with its defined edges and channels can still be tough.

Solutions Review editors will curate vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy big data and data management news items.

Kobai this week announced the launch of Saturn, a new offering designed to bring the power of the knowledge graph to data already stored in lakehouses. By creating a semantic layer that sits atop Snowflake and Databricks

Codeless knowledge graph platform supplier Kobai has announced the availability of Saturn, whichj it says is the industry’s first knowledge graph to harness the scale, performance, and cost efficiency of the Lakehouse architecture.