Omni review

Omni is a business intelligence platform for analyzing governed data. It combines AI chat with dashboards, spreadsheets, point-and-click analysis and a SQL editor, so teams can move between asking a question and working directly with the underlying data. Its semantic model is meant to give the AI business definitions and domain context, rather than leave every answer to a raw query.

The product description says users can ask questions, refine results and follow up while chat context carries over. They can also build visualizations with filters and drill-downs, use formulas and forecasting on live data, or write SQL with intelligent autocomplete. For sharing, Omni supports reports and dashboards; its embedded offering includes white-label analytics, SSO embedding, APIs and an MCP server.

That is a wide remit: reporting, analysis, modeling and embedding in one product. Whether it fits depends in part on how much of that toolkit a team needs—and what the sales quote costs.

Omni’s clearest strength is range. Teams can start with a conversational question, inspect results in a dashboard, model data in a spreadsheet or drop into SQL. That matters for organizations where business users and analysts need different ways to work with the same governed data, rather than a chat tool disconnected from reporting and query workflows.

The semantic model is also central to the pitch. Omni says teams can define core logic and add domain knowledge to give AI context. That offers a way to encode business meaning into analysis instead of relying only on how someone phrases a prompt. The product description also says chat context carries into follow-up questions, which can make an investigation less repetitive.

Other useful pieces include dashboard filters and drill-downs, spreadsheet formulas and forecasting on live governed data, and SQL autocomplete. For software companies, white-label embedding, SSO, APIs and an MCP server give Omni options beyond internal reporting. These are product capabilities, not proof that every team will get accurate answers or save time: the published sources do not include independent performance results. Still, the combination gives teams several routes from metric to investigation to shared report.

The biggest drawback is price opacity. The pricing information we found, checked November 7, 2026 and marked low confidence, lists no monthly or annual price, free plan or free-trial terms. It describes the offer as a custom sales quote, with pricing based on seats, data volume and feature tier. There is no published starting price to use for a budget comparison.

The same information leaves key limits blank: seat caps and usage caps are not published. AI use is metered in credits, but credit overage unit prices are not published. Embedded analytics is an add-on, and its price is also not published. That makes it hard to estimate the full bill from the available information, especially if a team expects broad AI use or plans to embed analytics in a product.

Omni’s broad feature set may be more than a team needs if it mainly wants dashboards or basic reporting. The sources do not specify which features require higher tiers, what usage thresholds apply, or how much implementation work the semantic model takes. Get a written quote that spells out seats, data volume, AI-credit rates, embedding costs and tier restrictions before comparing it with a replacement.

Omni does not publish a starting price, monthly or annual rates, or a free plan. According to the pricing information checked on November 7, 2026, organizations must request a custom quote. That quote is based on seats, data volume, and feature tier, so there’s no public tier-to-tier price jump to compare.

The main billing gotcha is AI: usage is metered in credits, but credit allowances and overage rates are not published. Embedded analytics is an add-on, and its price is also undisclosed. Seat and usage limits aren’t published either. That makes it difficult to estimate costs or compare plans before talking to sales.

Treat any budget as provisional until the quote spells out included seats, data-volume assumptions, feature access, AI credits, overage charges, and embedding costs. Pricing is listed as sales-quoted, so buyers who need predictable public rates—or a free plan to evaluate the product—may want to look elsewhere.

Plan for a modeling project, not just a dashboard transfer. Omni combines dashboards, spreadsheets, SQL, and AI chat with a semantic model that supplies business logic and context. Moving to Omni will likely mean mapping existing metrics and permissions into that model, then rebuilding reports and checking that results match your current definitions. The effort depends on how much logic lives in your existing BI tool; Omni’s public pricing information doesn’t state migration services or timelines.

For an exit, the published information doesn’t say what can be exported or in which formats. Confirm how to retrieve dashboards, spreadsheet work, semantic definitions, and any embedded configuration before committing. The product description lists SQL, APIs, and an MCP server, but doesn’t establish that these provide a complete migration path.

We don’t have Reddit posts or comments in the published material, so we can’t substantiate claims about why users leave. Ask Omni for export details and include them in the contract.