Iterate faster, ship securely
GrowthBook gives modern edtech product teams warehouse-native experimentation, feature flag controls, and product analytics for learning.
Trusted by 3,000+ companies worldwide
Built for teams that ship learning at scale
You’re competing for attention and responsible for learning over time. Traditional measures and limited rollout aren’t enough for modern edtech product development.
Transparent statistics your data team trusts
Education researchers and data scientists need to trust the results when optimizing for learning outcomes. Every GrowthBook experiment result is backed by visible SQL you can inspect, reproduce, and share. Choose Bayesian or frequentist analysis with sequential testing, plus CUPED and post-stratification variance reduction.
Target rollout to any student group, any platform
By classroom or cohort, language or learning stage, desktop or mobile. Set target rollouts by any attribute your data model supports without the complex engineering setup. Update JSON parameters, paywall layouts, onboarding flows, and content rules without shipping new code or waiting for app store approval.
Test AI prompts and agent quality at scale
GrowthBook lets you run experiments based on use cases and intent across system prompts and agents. Test with real learners, against metrics that matter: skill mastery, session completion, and retention. Roll back AI features instantly if engagement or safety guardrails are violated.
Secure learner data inside your infrastructure
GrowthBook's warehouse-native architecture means no student data, user profiles, or behavioral data ever leaves your systems. GrowthBook queries your existing warehouse — Snowflake, BigQuery, Databricks, Redshift, and more — with read-only access.
Enterprise-grade security and access controls
GrowthBook fits your risk profile and compliance requirements without slowing you down or complicating your setup.
Create a culture of experimentation
For Dev Teams
Ship faster with confidence, rollback instantly.
For Data Teams
Powerful stats, full control, trusted results.
For Product Teams
Run 5x more experiments, prove impact faster.
GrowthBook open-source platform
GrowthBook’s modular design works on top of what you have, or replaces what’s not working.
Integrates with your tech stack. Analyze your data where it lives. SQL visibility.
No migration required. No changing tools. We work with your tech stack.
Connect our MCP server to Claude Code, Cursor, VS Code, etc.
“We don’t need any code changes, we don’t need an app release. We just configure the new tests and launch right away.”
“Our goal was to consolidate everything into a single platform while saving money and ensuring compliance and security.”
“Being able to turn a feature on and off with a flip of a switch is fantastic... That’s so much easier than having to do a deploy or a roll-back.”
“Experimentation showed what customers actually do rather than what we assume they’ll do.”
“People only see the wins, but there’s actually greater value in avoiding losses. We’ve stopped changes that could have cost millions.”
"GrowthBook allowed us to uplevel our code, speed up decision-making, and focus on what we do best—building a world-class AI lending marketplace."
"The fact that we could retain ownership of our data was very, very important. Almost no solutions out there allow you to do that."
“GrowthBook lets us build experiments exactly how we want. The ability to target based on culture and geography, as granular as needed, is a major win for us.”
"The fact that GrowthBook offered us the ability to keep that data in-house was a key reason why we chose to work with them."
"The fact that GrowthBook offered us the ability to keep that data in-house was a key reason why we chose to work with them."
"The fact that we could retain ownership of our data was very, very important. Almost no solutions out there allow you to do that."
“GrowthBook lets us build experiments exactly how we want. The ability to target based on culture and geography, as granular as needed, is a major win for us.”
FAQs
GrowthBook never ingests or stores your learner data. The platform connects to your existing data warehouse — Snowflake, BigQuery, Databricks, or Redshift — and runs analysis there using read-only SQL. No student PII is extracted, transmitted, or processed outside your infrastructure. For teams with strict data residency requirements, GrowthBook can be deployed fully self-hosted or air-gapped. GrowthBook is SOC 2 Type II certified and COPPA, GDPR, and CCPA compliant.
Yes. GrowthBook supports rollouts and experiments based on any attributes your application already tracks. If your data model includes classroom ID, school, district, grade level, language, age group, or subscription tier, you can use those directly as targeting rules with no custom engineering required. This is how Khan Academy targets features to specific student cohorts and how Lingokids manages experiments across different learner segments.
AI assistants are non-deterministic, so the same prompt can produce different outputs across learner types, content domains, and age groups. GrowthBook lets you run controlled experiments comparing prompt variations, model choices, or agent configurations against the metrics that matter: skill completion, session success, retention, and response latency. You can set guardrail metrics on cost and latency so tradeoffs are made with data rather than guesswork. If a new AI feature underperforms or violates safety thresholds, you can roll it back instantly without redeployment.
Use GrowthBook's configuration-driven feature flags to control feature behavior dynamically via JSON parameters. Your team can update content rules, onboarding flows, paywall layouts, and AI prompt configurations without shipping new code or waiting on app store approval. Lingokids used this approach to run 15+ experiments per month, roughly double their previous velocity, with no additional release cycles.
Yes. GrowthBook works with the attributes and segments your platform already defines. Whether your audience is K-12 students in managed classrooms, adult learners on a self-directed path, or both, you define the targeting rules, metrics, and guardrails that make sense for each context. You can run entirely separate experiment configurations for different learner populations within the same platform.
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