智能体
siliconangle.com ·
@Maria Deutscher
Factory 为自改进软件开发平台融资 2 亿美元
Factory 宣布完成 2 亿美元融资,投资方包括 Blackstone、Khosla Ventures、Sequoia Capital、NEA 等机构,以及 Marc Benioff 等天使投资人。该公司利用 AI Agent 加速软件项目开发,但摘要未披露具体产品能力、客户规模或估值信息。
AI推荐理由 报道了 Factory 完成 2 亿美元融资,投资方包括 Blackstone、Khosla Ventures、Sequoia、NEA 及 Marc Benioff 等天使投资人,属于 AI 编程 Agent 赛道的明确融资事件;但摘要未披露产品技术细节、客户数据或估值,信息密度有限,'self-improving' 为厂商定位表述而非已验证能力。
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正文
UPDATED 20:19 EDT / SEPTEMBER 15 2026
AI
Factory raises $200M for its self-improving software development platform
by Maria Deutscher
Factory, a startup using artificial intelligence agents to speed up software projects, today announced that it has raised $200 million in funding.
The round was backed by Blackstone, Khosla Ventures, Sequoia Capital, NEA and several other prominent investment firms. They were joined by a group of angel investors that included Marc Benioff. Factory is now valued at $5 million, a $3.5 billion increase from April.
Factory, officially The San Francisco AI Factory Inc., offers a platform that can automate complex programming tasks such as porting an application to a new language. Developers interact with the software by entering high-level descriptions of the tasks they wish to perform. Factory breaks down each task to sub-steps and assigns them to a group of AI agents.
Under the hood, the platform automatically provisions infrastructure for each agent. It also performs related tasks such as preventing agents from inferring with one another’s work. A monitoring dashboard tracks project progress in real-time.
The starting point of Factory-powered software projects is a slash command called Readiness Report. It instructs the platform to check if the code repository being edited is agent-friendly. AI agents struggle to process code files that aren’t well-organized or lack technical explanations. Additionally, Factory checks whether the repository features guardrails that prevent agents from introducing vulnerabilities.
If everything is in order, the platform starts carrying out the coding task at hand. Factory assigns each step to the large language model that can perform it in the most cost-efficient manner. If the LLM is experiencing technical issues, the platform reroutes the request to a different algorithm.
Once a code snippet is ready, Factory runs it through a series of quality and cybersecurity checks. A feature called AutoWiki generates documentation that explains the code. It automatically refreshes the documentation after every update. Additionally, developers can configure an AI agent to monitor the code for technical issues and generate troubleshooting suggestions.
Factory runs agents in virtual environments called Droid Computers. Customers can deploy them in the cloud or on their own infrastructure. A Droid Computer saves the software libraries, configuration files and other technical assets used by the agents that it hosts. That removes the need for developers to manually install those assets before every session.
In January, Factory detailed that it’s using LLMs to automatically improve its platform’s AI agents. The models make enhancements based on anonymized usage signals collected from thousands of daily sessions.
“Across the world’s largest enterprises, we are seeing a move from individual coding agents to software factories that serve as the core foundation from which an entire software company operates,” said Factory co-founder and Chief Executive Officer Matan Grinberg.
The company disclosed today that its platform is used by hundreds of thousands of developers. Some of those users work at major tech firms such as Nvidia Corp., Adobe Inc. and Palo Alto Networks Inc. Factory will reportedly use its funding round to grow its headcount to 300 employees by year’s end.
Image: Factory
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