Omni
The AI analytics platform that grounds AI answers in a shared, governed semantic model.
By Omni Analytics · HQ San Francisco, US · 4.2/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Data teams buried in ad-hoc requests that want governed self-serve analytics with AI chat
- Product teams embedding white-label AI analytics into their own SaaS product via MCP and APIs
- Organizations already on Snowflake, BigQuery, Databricks, Redshift or dbt that want one shared semantic layer
- Companies that need AI answers to respect existing metric definitions and row-level permissions
Ideal size: 50–500 people · Scale-up with a data team and a cloud warehouse
Not for
- Teams with no cloud data warehouse and no data-modelling capacity
- Buyers who want a zero-setup BI tool with no semantic model to build or maintain
- Regulated organizations requiring on-premise or air-gapped deployment
- Very small teams shopping for a low-cost commodity dashboarding tool
Value metrics scorecard
Time-to-Value
Around 2 weeks to first governed insight
~14 days to first production value
Total Cost of Ownership
On request
Not published on the vendor site; sold as a quote-based subscription through sales.
Implementation Friction
3/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Not published
Add-on costs
- AI usage above organization credit caps is billed as overage.
Company & support
Who is behind Omni, and how your team gets help once it is live.
Company
- Founded
- 2022 · 4 yrs in business
- Headquarters
- San Francisco, US
How you get support
- PhoneNot listed
- EmailNot listed
- Live chatNot listed
- Support portal / ticketsNot listed
- Community forumAll plans
- Help centre / docsAll plans
- Dedicated account managerNot listed
- In person / on-siteNot listed
- Hours
- Not recorded
- Response time
- Not stated
Public documentation and community resources are the self-serve support surfaces described on vendor pages; support access to a customer instance is controlled and revocable by the customer.
“Not listed” means the vendor’s public pages don’t mention that channel, not that it is unavailable. Ask about it during evaluation.
Market position
Where Omni sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line.
Companies on the chart 6 / 10
- Omni
- Unito
- Tines
- HiBob
- LawVu
- Employee Navigator
Add or change companies
Up to 10 companies including Omni. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
Ships an official MCP server. Connects to Claude Code, Claude Desktop, ChatGPT connectors and Cursor out of the box.
AI & MCP readiness
What Omni ships in AI, and what it asks of your ecosystem.
AI features shipped
AI chat, dashboard summaries, workbook prompts and routines are grounded in Omni's semantic layer, which also enforces row-level security. AI Hub provides usage monitoring, evals and credit tracking, and an MCP server exposes the AI to external tools.
Your data & models
- Trains on your data
- Never trains on your data
- Runs on
- Anthropic, OpenAI, Google
- AI pricing
- Billed by usage or credits
In your ecosystem
- AI connection
- Official MCP server
- Model key
- Either
- AI usage audit
- Basic visibility
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Omni is a cloud business-intelligence platform built around a shared semantic model. Teams query data by chat, dashboard, spreadsheet, SQL or point-and-click, and an agentic AI layer plans queries, builds dashboards and summarises results. Because AI runs through the semantic layer, metric definitions and row-level permissions are enforced. Omni also ships an MCP server, REST APIs, embedding and white-labelling, and connectors to Snowflake, BigQuery, Databricks, Redshift, Postgres, dbt and more.
Frequently asked questions
What is Omni and who is it aimed at?
Omni is a cloud analytics and business-intelligence platform whose core is a shared semantic layer. It is aimed at data teams drowning in ad-hoc requests, at business users who want self-serve answers, and at product teams that want to embed or white-label analytics and AI into their own applications.
How is Omni's AI kept accurate?
The AI is grounded in Omni's semantic layer rather than raw tables, so it reuses existing metrics, joins, definitions and access controls. Users can add AI context, curate dataset instructions, run evals against real prompt sets, and see the SQL behind any AI response in a workbook.
Can we choose which LLM provider powers the AI?
By default Omni's AI runs on Anthropic's Claude models hosted on AWS Bedrock. Organizations can instead configure Anthropic Direct, Google Vertex AI, OpenAI, or Grok (xAI); custom provider API keys are stored per organization and are not exposed in the UI after saving.
Does Omni train models on our data?
Omni's security page states that data provided to the LLMs used by Omni, including metadata, is never used for model training. Query generation shares only metadata such as field names and filters; result sets are shared only when a user asks the AI to summarise a query.
Which data platforms does Omni connect to?
Omni has native connections to Snowflake, Google BigQuery, Databricks, Amazon Redshift, Postgres, ClickHouse, Trino, MySQL, MotherDuck and Microsoft SQL Server, plus a bi-directional dbt integration and PrivateLink/tunnel options for private networks.
Can we embed Omni in our own product?
Yes. Omni supports SSO embedding of dashboards, workbooks and apps, an Embed SDK, REST APIs and an MCP server. Product teams can white-label the experience and use the APIs or MCP server to bring governed querying into their own interfaces.