Product Overview of Freeplay
Freeplay is a comprehensive platform designed to empower product teams, including product managers, designers, domain experts, and developers, to efficiently prototype, test, and deploy Large Language Model (LLM) powered features. Here’s a detailed look at what Freeplay does and its key features:
End-to-End Workflow
Freeplay provides an end-to-end workflow that enables teams to iterate on prompts, monitor results, curate and label data, conduct evaluations, and automate testing. This integrated approach creates a continuous cycle of monitoring and improvement, streamlining the development process for LLM-powered features.
Prompt Management and Version Control
One of the standout features of Freeplay is its prompt management and version control system. This allows teams to manage and update prompts without the need for code deployments. Prompts are stored in a version control system, enabling easy switching between different versions of prompts and models across various environments, including development, staging, and production. This flexibility reduces the risk of errors and saves time.
Visibility and Observability
Freeplay logs LLM interactions as “sessions,” providing visibility into the entire customer experience. These sessions can be viewed, labeled, and saved for future testing. The platform includes an observability dashboard where teams can search, filter, and inspect results, including prompt versions, input variables, RAG contexts, LLM completions, costs, and latency. This comprehensive visibility helps teams understand exactly what is happening with their LLMs.
Automated Testing and Evaluation
Freeplay automates the testing and evaluation process, combining both AI and human-in-the-loop workflows. Teams can save test cases from observed customer sessions and replay them to test new versions of prompts or code. The platform supports automated evaluations using AI evaluators and human-labeled examples for correction and confirmation. This ensures fast, accurate, and relevant evaluations, allowing teams to ship features with confidence.
Data Curation and Labeling
Freeplay facilitates the curation and labeling of data sets for testing, fine-tuning, and other purposes. Team members can apply custom labels to sessions and save them as test cases, making it easy to build a comprehensive dataset for consistent testing. This integrated workflow eliminates the need for separate observability tools and enhances the efficiency of data management.
Developer Control and Integration
Freeplay offers developer SDKs for Python, Node.js, and Java (including all JVM languages), making it easy to integrate with existing stacks. The SDKs provide basic methods for simple integrations and support custom callbacks and overrides for more complex customizations. This ensures that developers can test LLM features end-to-end within their code, generating realistic results repeatably and at scale.
Enterprise-Ready
Designed with B2B software teams in mind, Freeplay is enterprise-ready from day one. It offers dedicated environments to protect data, access controls to manage team access, and fast, flexible developer integrations with minimal additional latency. This makes it suitable for teams that require robust security, control, and scalability.
In summary, Freeplay is a powerful tool that simplifies the process of working with LLMs by providing a collaborative, flexible, and automated environment for prototyping, testing, and deploying AI features. Its key features include prompt management, automated testing, comprehensive observability, and seamless integration with existing development workflows.