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About
Freeplay is a comprehensive operations platform purpose-built for AI engineering teams. It brings together every critical workflow—prompt and model management, custom evaluations, LLM observability, batch testing, and production monitoring—into a single, cohesive data flywheel designed to accelerate the path to product quality. With Freeplay, teams can version and deploy prompt and model changes like feature flags, enabling rigorous experimentation without engineering bottlenecks. Custom evaluations can be created and tuned to measure quality specific to each product's needs, while LLM observability provides instant search across any interaction from development through production. The platform's testing suite lets teams quantify the impact of every change through a customizable playground, batch tests and experiments, and automated eval runs. On the observability side, production monitoring with alerts, collaborative data review and labeling workflows, and dataset management tools help teams continuously improve their AI applications based on real-world feedback. Freeplay is ideal for AI product teams at startups and enterprises alike who need to move fast, maintain quality, and build a culture of continuous experimentation. It bridges the gap between engineers and domain experts, giving everyone the tools to contribute to product improvement.
Key Features
- Prompt & Model Management: Version and deploy prompt and model changes like feature flags, enabling controlled experimentation and rollback without code deploys.
- Custom Evaluations: Create and tune product-specific evals to accurately measure quality, then run them automatically across tests and production monitoring.
- LLM Observability: Instantly search, find, and review any LLM interaction across the full development-to-production lifecycle.
- Batch Tests & Experiments: Launch batch tests from the Freeplay UI or via code to measure the impact of every change to prompts and agent pipelines.
- Data Review, Labeling & Dataset Management: Multi-player workflows to analyze and label production data, identify patterns, and build golden datasets for fine-tuning and experimentation.
Use Cases
- AI engineering teams managing and versioning prompts across multiple LLM providers and product environments.
- Product teams running systematic A/B experiments on prompt changes to measure quality impact before deploying to production.
- ML engineers setting up automated evaluation suites to continuously monitor AI output quality in production.
- Domain experts and data labelers collaborating to review LLM interactions, annotate data, and build curated datasets for fine-tuning.
- Startups and enterprises building a data flywheel for continuous improvement of customer-facing AI features.
Pros
- End-to-end AI workflow in one platform: Freeplay covers the entire AI engineering lifecycle—build, test, and observe—eliminating the need to stitch together multiple tools.
- Collaborative by design: Supports both engineers and non-technical domain experts, making it easy for whole teams to contribute to AI product quality.
- Automated continuous improvement: Auto-evals, production monitoring, and alerts create a self-sustaining feedback loop that surfaces issues and improvements automatically.
Cons
- Primarily suited for LLM-based products: Freeplay is purpose-built for LLM applications, so teams working on non-language AI models may find limited applicability.
- May require setup investment: Getting the most from custom evals and the full observability suite requires initial configuration and integration effort.
Frequently Asked Questions
What is Freeplay?
Freeplay is an AI engineering operations platform that unifies prompt management, evaluations, LLM observability, testing, and production monitoring into a single continuous improvement workflow for AI product teams.
Who is Freeplay designed for?
Freeplay is built for AI engineering teams at startups and enterprises, including both software engineers and domain experts who need to collaborate on building and improving AI products.
Can I use Freeplay with any LLM provider?
Yes. Freeplay's customizable playground and integrations support multiple LLM providers, allowing you to craft prompts and compare results across providers in one place.
How does Freeplay handle evaluations?
You can create custom evaluations tuned to your product's quality criteria, run them manually via batch tests, or automate them to run continuously in production for ongoing monitoring.
Is there a free plan available?
Yes, Freeplay offers a free tier to get started, with paid plans available for teams that need advanced features, higher usage limits, or enterprise-grade support.
