20 Sept 2026
An open-weights release with a date, a name and an empty repository
A 600-billion-parameter flagship announced today says its weights arrive on 15 October. The repository named for them currently holds one…
Define "customer" once as governed SQL and query it like a table — a semantic layer built so the AI assistant answers from the company's own definitions instead of inventing a join.
Basedash Models is a semantic workspace released by Basedash on 19 September 2026. It addresses the oldest failure in company reporting: two teams counting customers differently, and nobody able to say which number is right. A model captures a concept the business actually runs on — customers, orders, active accounts — once, as reusable SQL attached to a data source, with its own editors for details, columns, measures and segments, plus relationships between models and written guidance on when each should be used. The SQL remains the source of truth; the workspace is where a team governs it. Once defined, a model is referenced in a query as though it were a table, so an analyst writes select * from models.customers rather than rebuilding the definition, and the company's AI assistant reads the same definitions — including the measures, the segments and the usage notes — when it generates SQL for a question asked in plain language. That is the substance of it for a buyer evaluating AI analytics: the assistant is constrained by definitions a human approved rather than guessing at the schema. The company describes it as the evolution of its earlier Definitions feature into a first-class product surface, and administrators can turn Models off for an organisation that is not ready for it. Two things to be clear about: this is a capability inside Basedash, not a separate product, and it is one of more than thirty launches the company has posted. No pricing is published for Models specifically, and none is recorded here. Basedash is a Y Combinator company founded in 2019.
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Updated 9/20/2026
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