Dot
Dot is an AI tool that allows you to chat with your Data Warehouse, providing fast and trustworthy answers to most business questions 24/7. It aims to free up d...
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What is Dot?
Dot is an AI-powered data analyst that answers any data question in seconds by letting users ask in plain English. It finds the right tables in your data warehouse, automatically writes SQL, and delivers a chart or table in about 30 seconds. This eliminates the need for dashboard hunting, query building, or waiting in an analyst queue for ad-hoc data requests.
Dot connects to major data warehouses including Snowflake, BigQuery, Redshift, and Postgres through no-code integrations. It also integrates with semantic layers like dbt and Looker, as well as communication tools like Slack and Teams. The platform uses a Context Agent that allows data teams to train Dot with company-specific business logic, metric definitions, KPI calculations, and terminology, ensuring answers are grounded in your organization's data model rather than hallucinating.
Dot is built for data teams but helpful for all users in an organization. It empowers business analysts, operations teams, and non-technical staff to get instant data insights without SQL knowledge. Data teams benefit by automating recurring reports and ad-hoc requests, freeing analysts to focus on deep work like data integration and quality control. The platform is SOC 2 Type II compliant, trusted by 100+ top teams including Duolingo, Airbyte, and Babbel.
Key features include automated charts and visualizations, scheduled email and Slack reports, workspaces for different teams, row-level security, SSO integration (Okta, Azure, Google), custom embedding for product analytics, and BI migration services. Dot is powered by OpenAI's and Anthropic's leading large language models, with data never used for training.
Dot pricing
Pricing model: Freemium
Credit-based pricing starting with 300 free one-time credits. Pro plan at $180 per month. No per-seat fees - you pay only for queries run with credits consumed per query based on complexity. Team+ plan includes workspaces, row-level security, SSO integration, and custom embedding features.
Dot pros
- Answers data questions in plain English without SQL
- Delivers answers with charts in about 30 seconds
- Connects to Snowflake, BigQuery, Redshift, and Postgres
- No-code integrations for data warehouses and semantic layers
- Context Agent trains Dot on company business logic and metrics
- No hallucinations - grounded by connected company data
- Scheduled email and Slack reports for recurring insights
- SOC 2 Type II compliant for enterprise security
- Row-level security to restrict data access by role
- SSO integration with Okta, Azure, and Google
- Workspaces separate data environments for different teams
- Custom embedding lets you embed Dot in your own app
- Credit-based pricing with no per-seat fees
- Free tier with 300 one-time credits to start
- Automated validation framework ensures trustworthy analytics
- Full auditability showing steps Dot took to reach results
- BI migration service helps migrate existing reports to Dot
- Improves over time through team feedback and usage
Dot cons
- No predictions or future forecasting capabilities
- Requires well-defined governed data model for optimal results
- Credit-based system means costs scale with query volume
- 300 free credits are one-time only, not recurring
- Best results require specific questions with timeframes
- Cannot answer questions about data not in connected warehouse
- May need retry if first attempt doesn't find results
- Learning curve for writing ideal questions with all components
Frequently asked questions about Dot
What is Dot and what does it do?
Dot is an AI data analyst that answers any data question in seconds. Instead of creating Jira tickets or waiting for analysts, you ask Dot questions in plain English like 'Revenue by channel?' or 'Conversion this quarter?'. Dot finds the right tables, writes SQL automatically, and delivers a chart in about 30 seconds with no dashboard hunting or query building needed.
How does Dot avoid hallucinations?
Dot ensures trustworthy analytics by basing answers on your company's data model and semantic layer, employing automated validation to check results, providing an evaluation framework for data teams to test performance, and offering full auditability that details every step Dot took to reach a result. Data is grounded by your connected warehouse, not general knowledge.
What data warehouses does Dot support?
Dot offers no-code integrations for data warehouses including Snowflake, BigQuery, Redshift, and Postgres. It also integrates with semantic layers like dbt and Looker, and communication tools like Slack and Teams. The platform automatically reads your schema and table structure during setup.
What is the Context Agent?
The Context Agent lets admins input business logic including metric definitions, KPI calculations, company-specific terminology, and custom rules that Dot applies when answering questions. This trains Dot on your company's business so it understands terms like 'Active Buyer' instead of just 'buyer' and applies your specific calculation rules.
How do I ask Dot questions for best results?
Ask clear and precise questions that include: which metrics (revenue, orders), what entity (suppliers, products), time period (last month, Q1 2024), granularity (daily, weekly, monthly), location/demographic (Region 1, Paris), and unit (Euros, kilograms). Be specific, provide context, clarify ambiguities, and use your company's business terminology from the business glossary.
What questions can Dot NOT answer?
Dot cannot provide future predictions or forecasts - questions like 'best selling product for next month' won't work. Questions without timeframes like 'What is our current revenue?' are too ambiguous. Questions that are too broad like 'Show me all orders ever placed' lack specific criteria. Dot also cannot answer about data not in your connected warehouse.
Is Dot secure for enterprise use?
Yes, Dot is SOC 2 Type II compliant with third-party audits by Prescient Assurance. All data is hosted on AWS with encryption at rest and in transit using TLS/SSL. Data sent to AI models is never used for training. Features include SSO, 2FA, role-based access control, quarterly access reviews, and vulnerability scanning. Data is hosted in US or Europe per GDPR/CCPA compliance.
How does the credit pricing work?
Pricing is credit-based with no per-seat fees. You start with 300 free one-time credits. Credits are consumed per query based on query complexity. The Pro plan is $180 per month. You only pay for queries actually run, making it cost-effective for teams that don't need unlimited queries or want to avoid per-user licensing costs.
Does Dot replace data analysts?
No, AI like Dot enhances productivity by automating specific tasks. Data teams still handle diverse responsibilities like data integration, quality control, and business guidance. Dot streamlines ad-hoc requests and automates recurring reports, freeing up engineers' time to focus on other hard problems and deep work instead of answering easy dashboard questions.
What features are in the Team+ plan?
Team+ plan includes workspaces for separate data environments for different teams or departments, row-level security to restrict what data each user can query based on their role, SSO integration with Okta/Azure/Google, and custom embedding to embed Dot inside your own app or product for offering AI analytics to your customers.