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As artificial intelligence drives unprecedented demand for data processing, a Mountain View startup is offering a solution to one of AI’s least discussed but most critical challenges: moving and transforming massive datasets quickly enough to keep up.
Voltron Data, which announced a strategic partnership with Accenture today, has developed a GPU-accelerated analytics engine that could help enterprises overcome the data preparation bottleneck hampering AI initiatives. The company’s core product, Theseus, enables organizations to process petabyte-scale data using graphics processing units (GPUs) instead of traditional computer processors (CPUs).
“Everyone’s focused on the flashy new stuff that you can touch and feel, but it’s that data set foundation underneath that is going to be key,” said Michael Abbott, who leads Accenture’s banking and capital markets practice, in an exclusive interview with VentureBeat. “To make AI work, you’ve got to move data around at a speed and pace you just never had to before.”
Building for the AI tsunami: Why traditional data processing won’t cut it
The partnership comes as companies rushing to adopt generative AI are discovering their existing data infrastructure isn’t equipped to handle the volume and velocity of data required. This challenge is expected to intensify as AI agents become more prevalent in enterprise operations.
“Agents will probably write more SQL queries than humans did in a very short time horizon,” said Rodrigo Aramburu, Voltron Data’s CTO and co-founder. “If CIOs and CTOs are already saying they spend way too much on data analytics and cloud infrastructure, and the demand is about to step function higher, then we need a step function down in the cost of running those queries.”
Unlike traditional database vendors that have retrofitted GPU support onto existing systems, Voltron Data built its engine from the ground up for GPU acceleration. “What most companies have done when they’ve tried to do GPU acceleration is they’ll shoehorn GPUs onto an existing system,” Aramburu told VentureBeat. “By building from the ground up…we’re able to get 10x, 20x, 100x depending on the performance profile of a particular workload.”
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The company positions Theseus as complementary to established platforms like Snowflake and Databricks, leveraging the Apache Arrow framework for efficient data movement. “It’s really an accelerator to all those databases, rather than competition,” Abbott said. “It’s still using the same SQL that was written to get the same answer, but get there a lot faster and quicker in a parallel fashion.”
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