Customer Impact

Trusted by data teams at leading companies

See how teams save thousands of hours and make better decisions with Dot.

Choco office
Choco logo

Choco digitizes ordering between restaurants and suppliers, helping the food supply chain move faster and with less waste.

3300h+

saved in yearly time savings from improved data access

18x

Return on Invest from the time saved using Dot for analytics

The self-service ability for our least technical and furthest operational stakeholders to answer questions by themselves has increased dramatically since implementing Dot.

Marina Begovic, Analytics Manager at Choco
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Duolingo office
Duolingo logo

Duolingo is the world’s most-used language-learning platform, known for rapid experimentation and data-informed product decisions.

12000h+

saved in yearly time savings

18x

Return on Invest from Dot

5000+

tables Dot is answering questions about

At Duolingo, we really believe in making data-informed decisions. This means that we want our data to be accessible to all of our employees (Duos), regardless of technical background.

Lavanya Aprameya, Senior Software Engineer at Duolingo
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Emerge office
Emerge logo

Emerge is a transportation spend and freight-procurement platform that helps shippers optimize contract and spot buying while accessing a large network of vetted carriers.

2000h+

saved in yearly time savings

10x

Return on Invest from Dot

99%

faster time to insight

Team members could just ask Dot a question in Slack and get the answer within seconds – the first time it happened, a lot of us were honestly amazed.

Jeff Albenberg, Director of Software Engineering, Emerge
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KRY office
KRY logo

KRY is one of Europe's leading digital healthcare platforms, offering digital and physical healthcare services across Sweden, France, the UK, and Norway.

€800K/yr

revenue opportunity identified from a single open-ended question

10 min

to identify, analyze, and size the opportunity

20+

hypotheses tested simultaneously across dimensions

We could have cut the funnel by age, by gender, by cohort, by dozens of dimensions. We just never had the time to do it systematically. Now we can.

Claire Bertrand, Data and Analytics Lead, KRY
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Benchmarked on 450+ financial analysis tasks from Adyen

You can train Dot to get better.

Add instructions, examples, and business rules with Dot's context agent.

Hours of analysis in seconds.

Dot vs trained human analysts at Adyen on standardized tasks.3

1 DABStep · 450+ multi-step financial analysis tasks by Adyen & HuggingFace.
2 Google Data Science Agent · ~52% weighted overall (Nov 2025).
3 Human baseline from DABStep: 62% accuracy, 3+ hrs/question on easy tasks.

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