Pricing + Benefits

Whether you’re a small startup or large organization, we’re here to help you get started.

Save 12% on annual billing
Starter
For teams exploring AI-powered analytics
Free
 
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  • 3 active tables
  • 100 credits + 10/month
  • Chat
  • Model
  • Evaluate
Standard
For data teams ready to scale self-serve analytics
$699
Per month
Start for Free
  • Everything in Starter +
  • Up to 15 active tables
  • Up to 500 credits/month
  • Live chat support
  • Priority onboarding
  • API access
Enterprise
For organizations that need full control and dedicated support
Custom
 
Book a Demo
  • Everything in Standard +
  • Unlimited admins & users
  • Unlimited messages
  • Self-hosted environment
  • Dedicated support
  • Custom training & onboarding
  • Fine-grained access control

50% off for startups with ≤30 employees, accredited NGOs, and university faculty. Contact us

Trusted by 100+ top teams

Duolingo
Airbyte
BlaBlaCar
Babbel
Choco
Flix

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.

Questions

ROI Calculator

200
3
$70,000
20
24

Return on Investment per annum2

$84,1041,168% ROI

99.9%

Faster time to insights

180

More people enabled3

1Dot is able to complete 80% of adhoc requests that would take an analyst less than 60 minutes to complete.

2The USD savings represents how much would have been spent on hiring analysts to serve this amount of questions. In most companies, the main advantage of Dot is that more stakeholders can get served, improving decision making across the company. These benefits are harder to quantify, but should usually be even higher (a decision that is made because of data can regularly affect revenue by up to 10%).

33% of all employees work directly in analytics. 7% of all employees are power users who know SQL or have a deep understanding of the data model. Therefore 90% are stuck with static dashboards that can’t answer a long tail of questions.