For years, the promise of a truly “self-driving” data platform has been hindered by the manual complexity of data engineering. Traditional ETL jobs, handwritten SQL and rigid orchestration frameworks were designed for a legacy era of static analytics, not the dynamic, high-velocity requirements of the AI era.
Today, the primary bottleneck for AI initiatives isn’t just processing data but the speed at which enterprises can author and maintain the trusted pipelines that feed AI models.
That’s why we’re excited to welcome the TensorStax team to Snowflake today. TensorStax has developed an innovative approach to autonomous AI for data engineering.
As TensorStax joins Snowflake, we’re energized by what this team will build next together — applying their talent and perspective to help shape a future where data teams can move beyond the day-to-day burden of manual pipeline work and focus on higher-impact problems.
From its inception, TensorStax was designed as autonomous AI for data engineering that could build pipelines, verify them programmatically and adapt as things changed.
As TensorStax’s founders spoke with customers, they quickly discovered a common theme: Teams were running Airflow, dbt, Snowflake and other tools side by side, and they needed systems that could reason across them all. TensorStax was born out of these conversations.
That customer-first mindset and ability to see across complex, real-world environments is what made the TensorStax team such a natural fit for Snowflake.
With this acquisition, we’re creating a unified environment where agentic AI can handle the heavy lifting of ingestion and transformation by treating pipeline code as a priority inside the Snowflake AI Data Cloud — freeing data engineers to shift their focus from writing individual functions to orchestrating intelligent ecosystems.
At Snowflake, we’re re-architecting the data platform for a world of agentic systems that run natively, securely and at scale. Our CEO, Sridhar Ramaswamy, has brought a startup mindset to the company, focusing on building with urgency. This mindset allows acquisitions to join the company and contribute quickly.
TensorStax’s specialized tooling, built to make agents effective at data engineering, is already living in Cortex Code, which we announced this week at BUILD London. It helps developers create the next generation of data and AI applications using systems that don’t just generate output but reason, verify and operate autonomously.
We’re excited to welcome the TensorStax team to Snowflake as we define a new category of autonomous data infrastructure built for the AI era.
For years, the promise of a truly “self-driving” data platform has been hindered by the manual complexity of data engineering. […]
Guided by the mission of simplifying data workflows for every builder, wherever they operate, Snowflake is unveiling a series of […]
AI innovation continues to transform applications and experiences across industries and enterprises. Companies are increasingly focused on driving measurable outcomes […]
Our services help both the big and small organisations in the identification of security breaches and provide outclass solutions to prevent any potential harm.