"Entire's tech has three components. One is a git-compatible database to unify the AI-produced code. Git is a distributed version control system popular with enterprises and used by open source sites like GitHub and GitLab. Another component is what it calls "a universal semantic reasoning layer" intended to allow multiple AI agents to work together. The final piece is an AI-native user interface designed with agent-to-human collaboration in mind."
"The first product Entire is releasing is an open-source tool it calls Checkpoints that automatically pairs every bit of software the agent submits for use in a software project with the context that created it, including prompts and transcripts. The idea is to allow the human developer to review, search, and perhaps even learn from why the AI did what it did."
Entire raised $60 million at a $300 million valuation to address management of code written by AI agents. The technology combines a git-compatible database to consolidate AI-produced code, a universal semantic reasoning layer to enable multiple agents to interoperate, and an AI-native user interface for agent-to-human collaboration. The initial open-source product, Checkpoints, pairs every submitted code artifact with the prompts and transcripts that produced it, enabling developers to review, search, and learn from AI decisions. Entire aims to reduce low-quality AI contributions and adapt version-control workflows to an AI-driven development era.
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