Description
GrowthOS is a platform designed to reconstruct and evaluate agent journeys in real-world scenarios. It focuses on understanding how agents discover, choose, and use products by reconstructing the task journey, which includes the agent's objective, the product surfaces encountered, and the evidence connecting these events. GrowthOS differentiates between production reconstruction and controlled Evals. While reconstruction describes real product behavior based on available evidence, Evals run defined tasks under controlled conditions to compare agents, models, environments, and product treatments. This approach allows for a comprehensive understanding of agent interactions and helps identify areas for improvement.
Read More
The platform requires data access depending on the task and surfaces involved, with a scoping call to identify the necessary evidence set. GrowthOS emphasizes the importance of evidence confidence, which qualifies the reconstruction process. It maintains separate metrics for production ATCR, Eval pass rate, and evidence confidence, ensuring that each measure answers different questions without collapsing them into a single score.
GrowthOS integrates with various product-owned evidence sources, including browser, docs, auth, API, MCP, CLI, SDK, and backend systems. It offers Python and TypeScript SDKs for instrumenting application and backend events. The platform's security measures include minimizing data before correlation, tenant boundaries, scoped identifiers, and pre-storage redaction.
GrowthOS is ideal for teams looking to improve their product's agent task completion rate by understanding real-world agent interactions and making data-driven improvements. It is trusted by teams at various companies and is led by a team of experienced founders with backgrounds in engineering and AI.
- CategoryAutomation & Agents
- Pricing ModelContact sales
- DeploymentCloud
- PlatformsWeb
GrowthOS's Core Features
Reconstruct agent journeys
Run controlled Evals
Measure production ATCR
Integrate with product-owned evidence
Python SDK for backend events
TypeScript SDK for browser events
Evidence confidence classification
Security and privacy controls
How to use GrowthOS?
Configure: Set up data access and evidence paths
Use: Reconstruct agent journeys and run Evals
Optimise: Analyze results to improve product interactions
Verify: Measure real-world outcomes post-implementation
GrowthOS's Use Cases
- Agent journey reconstruction
- Controlled task evaluations
- Product improvement insights
- Evidence-based decision making
- Security and privacy management
