The first diagnostic analytics platform
Kater makes it possible for executives to understand why business outcomes occur in a couple seconds. Kater generates informed hypotheses, validates those hypotheses through code, then surfaces the insights to the user to then make a final decision. Yvonne was a data engineer and analyst who built the entire data stack at CREXi. Robin led engineering in Microsoft. Data is the new oil. Kater is forging a future where decision-makers can uncover valuable insights that may have been previously limited by the scope of specialized data teams. This is the future of data.
Active Founders
Yvonne Chou
Yvonne is the co-founder and CEO of Kater. She graduated from UC Berkeley. Previously, she was a data engineer at Crexi, where she built the data infrastructure from the ground up. She has 8+ years of experience working in analytics teams for companies like Kaiser Permanente, Tapcart, and Crexi, where she supplied data to all dashboards for sales, marketing, finance, and executive management.
Robin Seitz
Robin is the co-founder and CEO of Kater. He graduated Magna Cum Laude from UCLA. Previously, he worked at companies such as Microsoft, Abbott and Paragon as a Software Engineer. He has 8+ years of experience working in different software engineering disciplines, including distributed systems, full stack engineering and big data.
Company Launches
TL;DR
Instead of Slacking the data team and waiting 4 days for an answer, use Kater to get the answer in 30 seconds. We make it possible for executives to understand why business outcomes occur, and even alert them before the outcomes happen again.
đź‘‹ Hey Everyone
We’re Yvonne and Robin. We have over 9 years working in data teams for companies like Microsoft, Kaiser Permanente, Crexi, and Abbott.
As data people, 80%-90% of our time was dedicated to low-level data requests. When really, the true business value of data comes from answering the “why” questions.
That’s why we started kater.ai — we are committed to automating these low-level questions, and empowering everyone in a company to answer “why” business outcomes occur. These are the million dollar questions that fundamentally change how businesses operate, and ones they’ve historically never been able to address.
🤔 Why Can’t Companies Answer “Why” Questions?
The existing enterprise data operation workflow is unscalable.
- Data teams receive 10-15 adhoc requests per day
- Companies spend on average $10.5 million/year in data analyst salaries
- Data is extremely messy
👨‍💼📊 Meet Butler: Your AI Data Agent
The solution:
Butler is an AI agent that organizes the chaos of data.
We found a new way to auto-document your data team’s tribal knowledge through generating a data map. Butler indexes and searches the data map using a AgentMesh Framework.
Butler helps generate hypotheses, writes the queries to validate those hypotheses, and finds any insights from the queries.
🧠Butler Continuously Learns
We use a combination of RAG and GenAI to capture any feedback users give to support future context for Butler.
đź”— The Set Up Process:
- Simply connect Kater’s website to your data warehouse.
- We’ll auto-generate descriptions for all your tables and columns, and immediately start building the data map for you.
- After you verify the data map is correct, in less than 10 minutes, you can start asking questions about your data and training Butler.
🙏 Our Ask
We currently support connections with Snowflake, Bigquery, and Microsoft SQL Server. If you have any of these (of even if you don’t, we can build a connector in 1 hour) and want to be able to query your data using English, reach out to us at support@kater.ai!