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Snowflake Summit 2025 took over the Moscone Center in San Francisco last week, and Zenlytic was right in the middle of all the action. Whether you met us on the expo floor or over a glass of sparkling champagne at Zoë Bar, one thing was clear: the AI analytics wave isn’t just coming... It’s here. And Zoë is the differentiator.

Zoë just leveled up. Discover how our AI data analyst now creates fully customized charts. From colors to chart types, based entirely on natural language prompts, providing smarter visuals and faster insights.

With intelligent workflows you can prompt and orchestrate workflows to accomplish simple, complex, and multi-step actions as your data coworker. Leveraging Zenlytic's complete intelligent analytics platform—with dashboards, reports, data explorer, and cognitive layer—analyzing data has never been more powerful.

By earning this designation, Zenlytic has proven that our Intelligent Analytics platform and Zoë, our AI data coworker, have met a core set of functional and interoperability requirements when integrating with BigQuery.

Missed the webinar? Here’s a quick recap of the key takeaways from our conversation with Data Science Connect (DSC)—and why intelligent analytics is the future of BI.

Why, why, why are we still waterfalling? Software engineers have moved on to agile development but data engineers haven't.

Data chat sharing makes it a lot easier for business and data people to collaborate and share insights.

We just launched a way to comprehensively review changes on one branch before deploying to another.

John Santaferraro, CEO and Head Research Analyst at Ferraro Consulting, published five best practices to maximize impact of AI for BI. He also provides the foundational AI enablers for Business Intelligence.

AI agents will play a vital role in software programming and cybersecurity, but they will also change enterprise workflows and business intelligence, experts say.

Learn how BI tools can help your retail company streamline operations, enhance customer experiences, and make smarter decisions with real-time insights.

The modern data stack (MDS) transformed how data teams work, providing more power and efficiency than ever before. Tools like dbt, cloud warehouses, and automated testing have streamlined many processes. But is the business actually realizing the benefits?

AI analyst is a co-worker - not a copilot - so everyone can have their own dedicated data analyst

We are thrilled to announce that Zenlytic, the world’s first self-serve business intelligence platform, has now integrated with Motherduck, the robust database built on top of DuckDB.

By partnering with Zenlytic, a software company building the first self-serve business intelligence platform, Ad Fontes Media was able to increase productivity of the data team so they could deliver more precise insights to its customers, faster, without having to hire more team members.

Explore how organizations can use business intelligence to strip away the intricacies of data and foster significant growth.

Host Tobias Macey interviews Ryan and Paul on why they are building a self-service BI platform

The cognitive layer is how Zenlytic provides reliable AI data analytics and the world's first self-serve business intelligence platform.

The Leading 100 are the innovative tech startups driving the future of brand to consumer.

Conversation with Murali Kallem where he reveals his six steps to self-serve

Self-serve analytics on Snowflake is now possible with Zenlytic, now a technology partner of Snowflake.

LLMs & Semantic Layer is transforming self-serve analytics, leaving previous generations of self-service analytics in the dust.

MBODY360 Harnesses Data Insights for Growth with Zenlytic

"Essentially Ryan told me about what he's building with Paul. I found that to be absolutely fascinating... And so here we are."

Data engineers and teams often face challenges in optimizing complex queries for efficient execution. Keep reading to learn how to improve SQL query performance.

"I definitely needed a self-service business intelligence tool that can provide me with all of the data that I need. Zenlytic has been a great resource and has been there when we need them."

"It's just so nice to log in any time of day and have up to the day accurate data. It's been a fun surprise for me just to have a better view into how our product has been selling. And like, men, women, by style, by size, by specific product, that's been a nice unlock for us through Zenlytic."

Paul, the CTO and co-founder of Zenlytics, discusses how LLMs and semantic layers enable self-serve analytics. He explains that self-serve is a spectrum that increases capabilities continuously based on the power of underlying technology. While large language models (LLMs) are powerful tools for understanding intent and distilling it into useful information, they require business context to be able to make correct decisions. This is where semantic layers come in - they encode important information like definitions, dimensions, joins, etc., ensuring correctness every time you calculate something. Companies without proper semantic layers often struggle with ad hoc SQL queries or outdated dashboards which can lead to errors in reporting. Warby Parker is a good example of a company that spends most of its data team's time refining their semantic layer to ensure consistency in metrics across stakeholders.