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Basedash

ANALYTICS
Velocity10.0

AI-powered business intelligence and database interface with chat-based data analysis, dashboards, and automations

www.basedash.com ↗

Basedash introduces semantic SQL Models and AI Sources — turning its analytics workspace into a governed data layer.

analyticsai-workspacesemantic-layerpublic-dashboardsgoverned-sql
◆Current state
Basedash is shipping at a high cadence on its core vision: an AI-first analytics platform where natural language queries are grounded in governed SQL. The recent releases add Models (reusable governed SQL definitions that any query can reference), AI Sources (a transparency layer showing which tables, charts, and SQL underpinned each AI answer), and Tasks (an AI that reads real data and produces prioritized action items). These aren't incremental feature additions — they're architectural pieces of what Basedash is building toward.
◆Where it's heading
Basedash is assembling the components of a governed AI workspace on top of operational databases: semantic models for shared definitions, public dashboard sharing for external distribution, subscriptions for recurring delivery, and AI Sources for auditability. The Grok Bot integration and 'Tasks' feature both point toward Basedash expanding beyond internal analytics into decision-support tooling for business teams.
◆Prediction
Models will gain version control and owner assignment, and the AI Tasks feature will move out of research preview with more configurable automation — triggering actions (not just surfacing them) based on metric changes.

◆Recent moves

  1. 4d ago

    Basedash introduces Models: reusable governed SQL as a semantic layer

    ⚡ SPARK

    Definitions in Basedash have been promoted to Models — a top-level workspace where teams maintain reusable, governed SQL for core business concepts that anyone can reference with `select * from models.<name>`. Legacy definitions references migrate automatically, but the conceptual shift is significant: this is a semantic layer, not just saved queries.

  2. 6d ago

    AI Sources: inspect every table, SQL, and row behind an AI answer

    ⚡ SPARK

    AI answers in Basedash now expose every source behind them — tables, definitions, charts, connections, web pages, SQL, and returned rows. This is the auditability layer that enterprise buyers require before trusting AI-generated analytics.

  3. 11d ago

    See the sources behind every AI answer

    Completed AI reasoning steps now collapse into a summary line ('Analyzed for 1m 12s') instead of leaving a long trace visible — a UX improvement that keeps the response front and center without removing the audit trail.

  4. 13d ago

    Introducing Basedash for Grok Bot

    Basedash is now available as a plugin in Grok Bot, allowing Grok users to query governed company data and list connected sources directly from a Grok conversation — continuing Basedash's pattern of embedding analytics in AI interfaces.

  5. 18d ago

    Redesigned home pages that get out of your way

    Dashboard and Automations home pages were redesigned with a 'Jump back in' recency section and an inline failed-run activity feed with visual status indicators — reducing the navigation overhead for teams that actively use multiple dashboards and automations.

  6. 21d ago

    Introducing public sharing: live dashboards for anyone

    ⚡ SPARK

    Public sharing lets anyone open, filter, and sort a Basedash dashboard or chart via a link without a Basedash account — a new distribution channel that changes how internally-built analytics reach external stakeholders like clients and investors.