Is Omni built by the people who made Looker?

Yes. Former Looker and Google leaders founded Omni in 2022, including Colin Zima and Jamie Davidson. Omni offers a dedicated Looker migration toolkit.

Does Omni have a free plan?

No. Omni offers a trial and demo but no published free plan. Additional AI usage costs $1 per credit beyond the included allowance.

Can Omni send reports and answers into Slack?

Yes. Omni's Slack Agent supports direct messages, mentions, and threaded follow-ups. Omni Routines can also send scheduled or alert-triggered reports to Slack.

All comparisons

Dot vs Omni

Dot works alongside your current stack with published pricing and no Looker migration. Omni can replace a BI platform.

What are the differences between Dot and Omni?

Showing 18 of 43 capabilities across 9 categories

01 / 10

Who can use it to get answers?

Built for business users, not just analysts

Dot: Yes. Conversational surface for non-technical askers
Omni: Partly. AI chat sits atop analyst-built models Source

02 / 10

Where can users receive answers?

Native Microsoft Teams app

Dot: Yes. Native Teams app alongside Slack
Omni: No. No Microsoft Teams integration found Source

Answers and reports by email

Dot: Yes. Email supports conversational answers
Omni: Partly. One-way, scheduled or alert reports only Source

03 / 10

Which data sources can it access?

Warehouse and database connectors

Dot: Yes. 31 integrations incl. Oracle, SAP HANA, Fabric
Omni: Partly. ~14 warehouses; no Oracle, SAP HANA, Fabric Source

Joins data across separate sources

Dot: Yes. Multiple sources in one workspace
Omni: Partly. Joins span topics; cross-connection unconfirmed Source

04 / 10

Which business context grounds its answers?

Grounded in LookML

Dot: Yes. Grounds in existing LookML, Looker keeps running
Omni: No. One-time migration off Looker, not live grounding Source

06 / 10

Who owns and maintains the business logic?

Context and apps use Git and pull requests

Dot: Yes. Every publish is versioned through Git and PRs
Omni: Partly. AI Hub suggests edits, scoped to Omni's model Source

Context remains portable if you leave

Dot: Yes. Readable context and apps stay in your repository
Omni: Partly. Git YAML migrates models between connections Source

07 / 10

Which outputs can it produce?

Multi-step investigations, not just lookups

Dot: Yes. Multi-step investigations, parallel sub-agents, plan shown
Omni: Partly. Single-turn chat with threaded follow-ups Source

Exports decks and PDFs

Dot: Yes. Narrated PowerPoint and PDF business-review decks
Omni: Partly. PDF/PNG/XLSX/CSV export; no PowerPoint Source

Runs Python for statistical work

Dot: Yes. Python analysis for statistical, investigative work
Omni: No. SQL and Excel-style formulas only; no Python Source

White labeling and embedded analytics

Dot: Partly. Dashboard embedding; limited white-label controls
Omni: Yes. White-label embedding with governed content Source

Notebook or IDE for analysts

Dot: No. No notebook/IDE; Python runs internally only
Omni: Partly. SQL editor only; no Python, not full IDE Source

08 / 10

Which governance and security controls are included?

Self-hosting available

Dot: Partly. Self-hosted option, Enterprise tier only
Omni: No. No self-hosted option; AWS SaaS only Source

09 / 10

What is the product built to become?

Purpose-built as a full AI analytics platform

Dot: Yes. Purpose-built for AI analytics across the full workflow
Omni: Partly. A modern BI and embedding platform adding AI

10 / 10

How do pricing and cost controls work?

Public, predictable pricing

Dot: Yes. Published per-tier prices; usage metered in credits
Omni: No. No plan prices published; sales-quote only Source

Hard usage limits, spend visibility, and ROI

Dot: Yes. Set usage limits; track spend and ROI
Omni: Partly. Seat or contract limits; ROI tracked separately Source

Free tier or trial

Dot: Yes. Free plan, no credit card required
Omni: Partly. Free trial/demo only; no always-free plan Source

Across all 43 capabilities

Dot36 supported2 partial5 not available

Omni22 supported12 partial9 not available

Category	Decision point	Dot	Omni
01 / 10Who can use it to get answers?	Built for business users, not just analysts	Yes. Conversational surface for non-technical askers	Partly. AI chat sits atop analyst-built models Source
02 / 10Where can users receive answers?	Native Microsoft Teams app	Yes. Native Teams app alongside Slack	No. No Microsoft Teams integration found Source
02 / 10Where can users receive answers?	Answers and reports by email	Yes. Email supports conversational answers	Partly. One-way, scheduled or alert reports only Source
03 / 10Which data sources can it access?	Warehouse and database connectors	Yes. 31 integrations incl. Oracle, SAP HANA, Fabric	Partly. ~14 warehouses; no Oracle, SAP HANA, Fabric Source
03 / 10Which data sources can it access?	Joins data across separate sources	Yes. Multiple sources in one workspace	Partly. Joins span topics; cross-connection unconfirmed Source
04 / 10Which business context grounds its answers?	Grounded in LookML	Yes. Grounds in existing LookML, Looker keeps running	No. One-time migration off Looker, not live grounding Source
06 / 10Who owns and maintains the business logic?	Context and apps use Git and pull requests	Yes. Every publish is versioned through Git and PRs	Partly. AI Hub suggests edits, scoped to Omni's model Source
06 / 10Who owns and maintains the business logic?	Context remains portable if you leave	Yes. Readable context and apps stay in your repository	Partly. Git YAML migrates models between connections Source
07 / 10Which outputs can it produce?	Multi-step investigations, not just lookups	Yes. Multi-step investigations, parallel sub-agents, plan shown	Partly. Single-turn chat with threaded follow-ups Source
	Exports decks and PDFs	Yes. Narrated PowerPoint and PDF business-review decks	Partly. PDF/PNG/XLSX/CSV export; no PowerPoint Source
	Runs Python for statistical work	Yes. Python analysis for statistical, investigative work	No. SQL and Excel-style formulas only; no Python Source
	White labeling and embedded analytics	Partly. Dashboard embedding; limited white-label controls	Yes. White-label embedding with governed content Source
	Notebook or IDE for analysts	No. No notebook/IDE; Python runs internally only	Partly. SQL editor only; no Python, not full IDE Source
08 / 10Which governance and security controls are included?	Self-hosting available	Partly. Self-hosted option, Enterprise tier only	No. No self-hosted option; AWS SaaS only Source
09 / 10What is the product built to become?	Purpose-built as a full AI analytics platform	Yes. Purpose-built for AI analytics across the full workflow	Partly. A modern BI and embedding platform adding AI
10 / 10How do pricing and cost controls work?	Public, predictable pricing	Yes. Published per-tier prices; usage metered in credits	No. No plan prices published; sales-quote only Source
	Hard usage limits, spend visibility, and ROI	Yes. Set usage limits; track spend and ROI	Partly. Seat or contract limits; ROI tracked separately Source
	Free tier or trial	Yes. Free plan, no credit card required	Partly. Free trial/demo only; no always-free plan Source
Across all 43 capabilities		Dot36 supported2 partial5 not available	Omni22 supported12 partial9 not available

Conclusion

Choose for the analytics stack you want to end up with

The decision is not only which tool answers questions today. It is which product can become your analytics platform over time.

Choose Omni when embedded BI and Looker migration are the project

SSO options with dedicated Okta, Entra, and Rippling setup guides
Its semantic layer syncs with dbt through git
Embedded analytics supports SSO and vanity domains

Watch out

Large workbooks can slow or destabilize. Users describe lag, editing delays, and occasional instability as workbooks add data, calculations, and dashboard complexity. ^[1][2]

Pricing

No published plan prices; quotes require a sales process
AI usage overage bills at $1.00 per credit, pooled account-wide
Free trial and demo offered; no confirmed always-free plan

Source

Choose Dot for best-of-breed AI analytics that can replace BI

Connect Dot to the data sources and semantic models you already have, then start with one agent. Context, apps, and business logic stay version-controlled in a repository you own, so they never become a Dot-only asset. Add dashboards, reporting, and governed workflows as adoption grows, then retire BI software you no longer need.

Watch out

Dot is growing quickly. Its smaller team may not offer the same level of hands-on support as a larger vendor in every region.

Pricing

Free plan, no credit card
Pro at $200/month, or $180/month billed annually. Unlimited users.
Team at $800/month, or $720/month billed annually. Adds single sign-on and row-level security.
Enterprise is custom: self-hosting, SLAs, and volume terms

Full pricing

Why the pricing model matters

Frontier AI has variable inference cost. A vendor that relies only on seat pricing must eventually meter AI, absorb the cost, or limit capability. Dot makes usage visible, lets teams set limits, and tracks the return on that spend.

Receipts

Benchmarked against human analysts, and measured in production

DABStep is Adyen’s public data-analysis benchmark. Dot scored above trained human analysts. It is independently published and available to inspect. In production, customers report these outcomes.

18× ROI

Choco, from time saved on analytics

12,000+ hours

saved every year at Duolingo, across 5,000+ tables

99% faster

time-to-insight at Emerge

€800K found

in a single investigation at KRY

Every Dot answer shows its work. Click any number to inspect the query.