Kite was a developer tool that provided AI-powered code completions for programming languages such as Python, JavaScript, and Java. Founded in 2014 by Adam Smith, the company aimed to reduce boilerplate coding by analyzing local codebases and suggesting relevant snippets. The tool integrated with popular editors like Visual Studio Code, PyCharm, and Sublime Text, and it gained a significant user base among developers seeking faster coding workflows.
Kite's underlying technology relied on Machine learning models trained on open-source code repositories. Unlike later Large language model-based assistants, Kite used a combination of static analysis and local indexing to provide completions without sending code to the cloud, addressing privacy concerns. The company also developed a free desktop application that worked offline, which distinguished it from many contemporary cloud-based services.
History and Development
Kite was launched in 2014 by Adam Smith, who previously worked at Google and had experience with developer tools. The company raised over $17 million in funding from investors including Peter Thiel and Y Combinator. In 2016, Kite released its first public version, which supported Python completions. Over the following years, it expanded to support multiple languages and integrated with major code editors.
In 2018, Kite introduced a feature called "Intelligent Snippets" that used Deep learning models to predict multi-line code patterns. The company also published research on code completion using Neural network architectures, contributing to the academic field of program synthesis. However, despite its technical innovations, Kite struggled to monetize its free product, and it faced increasing competition from cloud-based AI assistants.
Technology and Features
Kite's core engine used a custom Sequence-to-Sequence (Seq2Seq) model to predict the next tokens in a code file. The model was trained on a large corpus of Python and JavaScript code, and it incorporated context from the user's current file and project. Kite also offered a feature called "Line-of-Code Completions" that could generate entire function bodies based on a comment or function signature.
One of Kite's notable features was its local processing architecture. The tool ran a lightweight server on the user's machine, which indexed the local codebase and served completions with low latency. This design allowed Kite to work offline and avoid sending proprietary code to external servers, a key selling point for enterprise users. Additionally, Kite provided a command-line interface and a web-based dashboard for tracking usage statistics.
Discontinuation and Legacy
In November 2022, Kite announced that it would shut down its services, citing the rapid advancement of Generative AI models like OpenAI's Codex and GitHub Copilot. The company's founder, Adam Smith, explained that the emergence of large language models had made their approach obsolete, as these models could generate more accurate and context-aware completions. Kite's website and desktop app were taken offline on December 1, 2022, and the company recommended users migrate to alternatives.
Despite its closure, Kite's influence persisted in the developer tools ecosystem. Its emphasis on local processing and privacy-aware design inspired subsequent tools that offered on-device AI assistance. Kite also contributed to public datasets and research on code completion, which were later used by academic groups and commercial products.
Reception and Impact
During its active years, Kite received positive reviews for its ease of use and speed, particularly among Python developers. It was praised for reducing repetitive typing and helping beginners learn syntax. However, some users noted that its completions were sometimes inaccurate or too generic, and the tool occasionally slowed down on large projects.
Kite's shutdown was widely discussed in developer communities as a sign of the disruptive impact of Transformer (architecture)-based models. The company's story is often cited as an example of how specialized AI tools can be overtaken by general-purpose models trained on massive datasets. As of 2024, no direct successor to Kite exists, but its approach to local code analysis has been incorporated into newer tools that combine on-device processing with cloud-based models.