Sundial is an AI-driven data analytics platform designed for product teams, growth marketers, and data analysts at startups and tech companies. It simplifies experimentation workflows and enables teams to analyze metrics, track experiments, and uncover performance insights—all without needing extensive SQL knowledge. Built with a focus on speed and collaboration, Sundial helps teams run faster product cycles and make confident, data-informed decisions.

Key benefits of Sundial include:

• Instant, AI-assisted data exploration

• Centralized experiment tracking with context

• Simplified access to product and marketing metrics

What are the key features of Sundial?

AI-powered insights for faster analysis

Sundial uses generative AI to speed up data interpretation and reduce dependency on SQL or analytics teams. The platform enables users to ask plain-language questions and get structured, visualized responses almost instantly.

• Ask natural language questions about your data

• AI generates dashboards, charts, and summaries automatically

• Speed up decision-making with contextualized answers

This functionality helps non-technical teams get immediate clarity from complex data without needing to write queries or wait for analysts.

Centralized experiment tracking and analysis

One of Sundial’s core capabilities is simplifying the process of managing and learning from experiments across teams. Instead of scattered spreadsheets or disconnected dashboards, Sundial provides a unified view of all tests in progress or completed.

• Log and categorize A/B or multivariate experiments

• Automatically calculate performance metrics and statistical significance

• Link experiments to goals, cohorts, and feature flags

This makes it easier for cross-functional teams to stay aligned on what’s being tested, why, and what outcomes were achieved.

Metric libraries to reduce redundancy

Sundial introduces a shared metric library concept, which creates a single source of truth for commonly tracked KPIs. This prevents discrepancies in metric definitions across teams and reduces the time spent recreating the same reports.

• Define core metrics once and reuse across dashboards and reports

• Consistent metric definitions reduce confusion

• Easier onboarding for new team members with pre-defined metrics

This feature is especially valuable for scaling companies with growing product, data, or growth teams.

Integrations with modern data stacks

Sundial connects directly to modern data warehouses and feature flag tools to streamline the analytics workflow. This eliminates the need for manual exports or engineering support when running product experiments.

• Native integrations with Snowflake, BigQuery, and dbt

• Syncs with feature flag tools like LaunchDarkly and Statsig

• Ingests product metrics directly from warehouse sources

These integrations allow users to start analyzing data and experiments quickly, using infrastructure they already rely on.

To summarize

Sundial’s strengths lie in accelerating decision-making, simplifying experiment workflows, and promoting consistency in how product and growth teams use data. Key advantages that make Sundial stand out from traditional BI or experimentation tools include:

• Faster insights through natural-language, AI-powered analytics

• Centralized experimentation tracking that scales with your organization

• Consistent metrics that reduce duplication and confusion

• Seamless integration with data warehouses and product tooling

Sundial is particularly suited for product-led, data-informed teams that need to move fast without compromising on analytical depth or accuracy.