When enterprise teams experiment with AI today, they rarely start from scratch. More often, they begin with fragmented data spread across cloud buckets, SaaS tools, legacy databases, and on-prem infrastructure each governed by different policies, formats, and stakeholders. For most organizations, this patchwork isn’t just a nuisance. It’s the bottleneck standing between AI pilots and real production use.
That infrastructure problem is where Starburst is placing its bet.
The Boston-based data platform, known for its open-source roots in Trino and distributed SQL analytics, is expanding its scope. This week, the company announced a set of AI-focused upgrades across its two core products, Starburst Enterprise and Starburst Galaxy including a new built-in agent, vector-native AI sear
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