Doram vs Omni
Omni is a full BI tool whose AI works through its model. Doram is a context layer that any AI can read, with its own analyst.
DoramChecked on 17 October 2026. Every fact about Omni comes from its public website and docs. The links are at the end.
The short answer
Omni is a full BI tool built on its own semantic layer. It has dashboards, spreadsheets, SQL, chat and a Slack agent, and its AI picks fields from the model while Omni’s engine writes the SQL.
Doram is a context layer first. It learns what your business means from your data, documents and tools, and every AI you use reads the same approved rules. Doram has its own analyst too, but the shared understanding is the core.
At a glance
| Question | Omni | Doram |
|---|---|---|
| What it is | A BI tool with a semantic layer and an AI agent | A context layer with its own AI analyst |
| Who builds the model | Built from your schema, then edited by your data team. An agent can draft parts. | Doram drafts it. Your team approves what matters. |
| What it reads | Schema, query history on Snowflake and Postgres, dbt, Looker (beta), chats | Schema, query history, dashboards, docs, Slack, Jira, CRM |
| How the AI gets the number | The AI picks fields. Omni’s engine writes the SQL. | The AI picks approved facts. A semantic compiler writes the SQL. |
| Review before changes go live | A modeler promotes changes. Pull requests are optional. | Review by risk, with the evidence and impact of each change |
| Other AI tools | MCP for Claude, ChatGPT and Cursor, plus a REST API | MCP and API |
| Where it runs | Omni cloud only | Doram Cloud, or your own cloud account |
What Omni does well
- The AI goes through the model. In Omni’s words, “The AI does not generate raw SQL directly from text.” A query engine writes the SQL, and a second agent checks the work before the answer goes out.
- It learns from use, with a person in the loop. After a chat, Omni can suggest new descriptions, synonyms or measures. You accept, edit or reject each one before it applies.
- A complete BI tool. Dashboards, spreadsheets, a SQL editor, chat, Slack, scheduled reports and apps all sit on one model. Omni also published a benchmark: 95 of 100 questions right, on its own data, and it calls the numbers “directional”.
Where they differ
Where the rules come from
Omni builds the first model from your schema, and its agent can add more from files or screenshots. It reads query history on Snowflake and Postgres, imports dbt, and is adding Looker. It also learns from chats and thumbs up or down.
Omni’s founders say customers feed in Notion pages, Google Docs and meeting notes. As far as its docs show, this is not yet a documented feature. We found no sign that Omni reads Slack, tickets or the CRM to build the model.
Doram reads those places on purpose. A Jira ticket, a Slack thread or a line in the CRM often holds the reason behind a rule. Doram turns these into rules, keeps the evidence, and sends them for review.
How changes are approved
In Omni, a person with Modeler rights promotes a change to the shared model. No second approver is required, and Git pull requests are off by default. The modeling agent has a review mode, but its auto mode applies changes at once.
Doram routes each change by risk. A new word for an existing metric goes live on its own. A change to how net sales is counted waits for its owner. Each suggestion shows its evidence and every metric it would change.
How the number is made
Both keep the AI off raw SQL for chat answers. Since late September 2026, Omni’s agent can also write raw SQL on a SQL tab you are viewing.
In Doram, the AI never writes the SQL. It picks approved facts, and the semantic compiler writes the query. Any past answer can be replayed on the version that made it.
Access and where it runs
Omni can run each query as the real user on BigQuery, Databricks and Snowflake, so your warehouse rules apply. It has row rules of its own, and masking is done by hand in the model. It runs only in Omni’s cloud.
Doram reads your warehouse grants at every sync, and masks or hides personal columns. When two rules disagree, the stricter one wins. It runs in Doram Cloud in the region you pick, or in your own cloud account.
Who should pick which
Pick Omni if you want a full BI tool with dashboards and spreadsheets today, your data team will own the model, and a cloud-only service suits you.
Pick Doram if your rules live in queries, documents and tools, you want them found for you and approved by their owners, and you want every AI in the company to read the same rules.