Anaconda is moving beyond Python package management with its acquisition of Kilo Code, an open-source, model-agnostic AI coding platform used by more than three million developers. The deal follows Anaconda’s acquisition of AI orchestration company Outerbounds earlier this year and adds AI coding to its growing enterprise AI platform.
The acquisition highlights a broader shift in enterprise AI. Companies are no longer looking for standalone coding assistants. They want platforms that can support AI development from start to finish. With Kilo, Anaconda is extending its platform into the developer’s IDE while continuing to build toward a broader stack that includes AI orchestration, governance, and production deployment.
“Every enterprise we talk to is asking the same question: how do we let our builders move as fast as AI now allows, without losing control of what ships or failing a compliance audit,” said David DeSanto, CEO of Anaconda. 
“Kilo is where that question starts, at the moment a builder writes the first prompt. Our job is to make sure that whatever an agent builds from that point forward runs on a foundation enterprises can trust, all the way to a future where that trust has to hold at the scale enterprises require without compromising on security.” 
(Shutterstock/ForestGraphicScaled)
Kilo gives Anaconda an AI coding platform that works across VS Code, JetBrains, the web, and the command line. It supports more than 500 AI models. This includes both commercial and open-weight models. It enables organizations to self-host the platform instead of relying on a single AI provider. Anaconda said Kilo processes trillions of AI tokens each month.
What’s in it for Anaconda? The acquisition fills another piece of the enterprise AI puzzle. The company is best known for Python and open-source software, but it has been steadily expanding into enterprise AI. Kilo adds AI coding to that mix. It provides customers with more options to build AI applications while keeping development inside the same enterprise environment.
On BigDATAwire, we covered the Outerbounds acquisition and how it brought AI orchestration to Anaconda. Kilo adds another piece. It brings AI coding into the platform in a way that Anaconda is now involved much earlier in the AI development process.
“Kilo and Anaconda are a rare fit: almost no overlap, and what each of us lacks, the other already has,” said Sid Sijbrandij, co-founder of Kilo Code and co-founder & executive chair at GitLab. “Kilo has many enthusiastic users doing agentic engineering with the freedom to use any model and any provider. Anaconda spent over a decade building enterprise trust; from packages to secure environments. The combination complements each other very well. I’m delighted Kilo was acquired by Anaconda.”
The details on product integration have not been made available by Anaconda yet. However, users of the platform should not expect too many immediate changes. Kilo is expected to continue to operate with its existing products and support while the company works toward deeper integration with the Anaconda platform. 
(Iurii-Motov/Shutterstock)
According to Anaconda, the goal is to connect the AI coding experience with the governed packages and development environments already available through its platform. Those deeper capabilities are a direction that the company is steadily building toward rather than just features available today. 
AI coding is becoming a crowded market. However, it is worth noting that the competition is shifting beyond who has the best coding assistant. Companies are now trying to build larger AI development platforms that combine coding, governance, orchestration, and deployment into a  unified platform. This means their customers don’t have to stitch those pieces together.
DeSanto said many enterprises are stuck between two extremes. Some standardize on a single AI model provider to keep everything under control. Others let developers use whatever AI tools they want. This makes it difficult to track security and compliance across the organization. Anaconda believes enterprises want the flexibility to choose different models for different tasks without giving up visibility or governance.
That challenge is becoming more common as AI moves from experimentation into production. Rather than competing solely on coding assistants or foundation models, vendors are increasingly trying to build platforms that manage the entire AI development lifecycle. The Kilo acquisition is another step in that direction as Anaconda continues expanding beyond Python and package management into enterprise AI development.
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