In a seed funding round led by Conviction Ventures and Matchstick Ventures, startup Freeplay has raised $3.25 million as it emerges from stealth mode. Founded by former Twitter employees, Freeplay aims to provide product development teams with the necessary tools to prototype and enhance software features that are powered by large language models (LLMs), such as ChatGPT and Meta’s Llama 2. The goal is to enable companies to integrate LLMs into their products effectively, ultimately delivering improved customer experiences.
Key Takeaway
Freeplay, a startup founded by ex-Twitter employees, has raised $3.25 million in a seed funding round to help companies build, experiment, and test apps powered by large language models (LLMs). Their platform streamlines the adoption of LLMs for product development teams, providing a comprehensive set of tools and features that enable prototyping, metrics tracking, and custom evaluations of LLMs. Unlike competitors, Freeplay caters to cross-functional teams and covers the full development lifecycle, offering control to developers while meeting the needs of a range of talents and backgrounds.
Streamlining AI Adoption for Product Development Teams
Freeplay was co-founded by Ian Cairns and Eric Ryan, who previously worked together at Gnip, a social media API aggregation company acquired by Twitter in 2014. Cairns, formerly leading the developer platform at Twitter, and Ryan, the senior director of engineering at Twitter’s Boulder office, witnessed the challenges faced by enterprises in embracing LLMs. They identified the need for new tools and development practices to assist software-as-a-service companies in adopting LLMs and continuously improving their applications.
Freeplay’s Comprehensive Platform and Features
Freeplay’s platform combines developer integrations with a web-based dashboard, providing teams with the ability to monitor user interactions, cost estimates, and app latency associated with AI-powered apps. Additionally, Freeplay offers beginner-friendly features that allow users to experiment with different prompts and swap models from various vendors. The platform also hosts tools to help identify and implement custom evaluations of LLMs, leveraging automated testing tools powered by LLMs, combined with human labeling workflows.
Standing Out in a Growing Market
While there are other AI-focused observability platforms and tools for tracking and sharing prompts, Freeplay sets itself apart with its end-to-end workflow that caters to cross-functional teams and covers the full development lifecycle. Many existing tools on the market target individual developers or focus solely on experienced machine learning and data science teams. Freeplay aims to bridge this gap by providing a comprehensive toolset that offers developers the necessary control, while also meeting the needs of diverse teams within larger organizations.
With the funding secured, Freeplay plans to expand its workforce and further develop its core product, driving innovation and empowering more companies to harness the potential of LLM-powered AI models.
