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Omni

ANALYTICS
Velocity6.3

Business intelligence and embedded analytics platform

omni.co ↗

Omni ships weekly, and almost every week the headline item is an AI feature

business-intelligencesemantic-modelai-routinesmcpdbtembedded-analytics
◆Current state
Omni publishes a dated weekly digest whose body is a single line listing that week's items, so each entry compresses several releases into a sentence. Across seven consecutive weeks the pattern is unmistakable: AI-powered semantic model generation reaching general availability, AI Routines creatable from chat and deliverable to Slack, AI model suggestion endpoints, AI credit controls scoped to embed entity groups and individual users, AI Evals support on Azure, and MCP surfaces appearing both in-app and as a searchDashboards tool. The non-AI items are steady BI plumbing — OAuth and GitHub App authentication for dbt connections, mobile dashboard settings, map legend positioning, presentation mode.
◆Where it's heading
Two things are happening in parallel and they are related. Omni is pushing AI into the modelling layer rather than only the query layer, which is what semantic model generation reaching GA signifies — the artifact that normally takes an analytics engineer weeks is being generated. At the same time it is building the commercial and access controls that AI features require: credit limits per user and per embed entity group arrived within weeks of the AI capabilities that consume them. The MCP work points at a third direction, exposing Omni's content to external agents rather than only serving its own chat.
◆Prediction
Credit controls appearing so soon after the AI features suggests consumption limits will keep expanding to cover newer surfaces, and with searchDashboards shipped as an MCP tool, more of Omni's catalog is the obvious next thing to expose that way.

◆Recent moves

  1. 8d ago

    Omni adds presentation mode and a searchDashboards MCP tool

    Full-screen presentation mode for content, delivery personalization modes, and a searchDashboards MCP tool. The MCP addition is the one that matters for direction — it makes Omni's dashboards discoverable by external agents rather than only by its own interface.

    View source ↗
  2. 15d ago

    Omni adds AI credit controls per user and embed entity group

    AI credit limits scoped to embed entity groups and to individual users, plus AI Evals on Azure and map legend positioning. The credit controls arrive two weeks after semantic model generation went GA, which is the sequence of a vendor metering a feature once customers can actually consume it.

    View source ↗
  3. 22d ago

    AI semantic model generation goes generally available in Omni

    ⚡ SPARK

    The GA clause buried in a weekly digest is the most consequential item across these seven weeks — everything after it, particularly the credit controls, reads as consequence. It moves Omni's AI story from assisting queries to producing the modelling layer those queries run against.

    View source ↗
  4. 29d ago

    Omni adds AI suggestion endpoints and OAuth for database connections

    AI model suggestion generation exposed as endpoints, mobile dashboard settings, and OAuth for database connections. Exposing suggestions through an API rather than only the UI fits the same pattern as the later MCP work — making Omni's AI reachable from outside Omni.

    View source ↗
  5. 1mo ago

    Omni brings AI routines to Slack and adds in-app MCP settings

    The shortest digest in the window, carrying Slack delivery for AI routines and in-app MCP settings. Both extend existing features to new surfaces rather than adding capability.

    View source ↗
  6. 1mo ago

    Omni adds AccessBoost for Apps and dbt deploy-token auth

    AccessBoost for Apps, HTTPS deploy-token authentication for dbt, and filter suggestions in dashboard properties. The dbt authentication work continues across several weeks here, later adding GitHub App auth and OAuth — a sign that connection security was a sustained project rather than a one-off.

    View source ↗