Home Platform AI Workspaces Trusted building blocks and AI agents, in the tools you already use. The AI Assembly Tax Before the real work starts, there’s the other work: the setup you rebuild for each new project. Setup Comes First, Again Your Best Idea Loses Momentum The hours go into rebuilding the foundation — not into the idea that started the project. Moving Fast Shouldn't Break Policy You shouldn’t have to choose between shipping fast and staying inside policy — or sit in a review queue to find out which one wins. You Want Speed. Your Company Wants Proof. Ecosystem Partners One Workspace. Your Way of Building. Start With Trusted Building Blocks Stop rebuilding your foundation. The packages, models, and environments are already vetted and ready — approved before you go looking for them. Packages : vetted, with provenance Environments : reproducible dev to prod Models : curated, routed to control spend Build Where You Already Work AI development isn’t confined to one interface. Work from your IDE, notebook, CLI, or desktop — connected to the clouds and data platforms you’ve already chosen. Your model and infrastructure choices stay open. Desktop, CLI, Notebooks, IDEs, cloud AWS, Google Cloud, Azure, NVIDIA Databricks, Snowflake, GitHub, GitLab Open models, without lock-in Keep Your Agents Inside Policy Give agents access to the tools and data they need while keeping permissions governed and activity auditable. Enterprise controls determine what agents can access and what actions they can take. Governed access : control agent access to tools and data Auditable activity : maintain visibility into agent actions Policy-driven controls : keep agents operating within enterprise policy New to anaconda Now Build Alongside AI

Development is getting more agentic. Kilo brings AI-powered coding right into your workspace, next to the packages, models, and tools you already use. Three Steps to a Demo Built Around You What Changes Once You're Not Assembling Platform & Security Teams Innovation without a new stack to run. Control without becoming the gate. You see what’s entering AI development without another manual review. More ideas get out of experimentation and into production — because the foundation stopped being the thing slowing them down. Less Assembly, More AI Search for packages Start with ready building blocks Hunt for models Discover models in one place Configure environments Start in ready environments Manually recreate environments for production Move from local to prod, reproducibly Move from local to prod, reproducibly Navigate disconnected tools Work from a consistent foundation Code everything manually Build alongside AI agents Add controls afterward Build on an enterprise-ready trusted foundation What Will You Build Next? Complete the form, and we’ll reach out within 1 business day to discuss your requirements. Then, we’ll build a demo that addresses your real challenges. Frequently Asked Questions Yes. No new execution model, no forced migration. Keep VS Code, JupyterLab, PyCharm, or Spyder. Point your IDE at the Python interpreter inside your conda environment, and your packages and dependencies follow. Kilo Desktop launches your IDE and manages environments without touching the command line, or use CLI when you need it. Quick-Start Environments resolve setup conflicts in one step so you get to work faster. Not the way it probably does now. You don’t file a request with the security team and wait to find out what you’re allowed to use — the packages you can reach have already passed policy. Your administrators set that policy once: a channel filtered by CVE score, CVE status, license type, platform architecture, and package name. It re-runs on each update, so no one reviews it by hand each time you need a new package or model, and any vulnerable packages are updated automatically. Available on Business or Custom plans. No. AI Workspaces works across open and closed models, the clouds and data platforms you’ve already chosen, and the IDEs and tools your team already uses. Auto-route models to control spend without losing the ability to change them later. The foundation stays consistent; the choices stay yours. The people doing the building — developers, data scientists, and AI practitioners who’d rather start on trusted ground than build it themselves. It also serves the platform teams who own that ground and get one governed source instead of another stack to run. And the security teams, who get a secure AI supply chain with SBOMs and CVBE tracking to see what’s entering AI development and block when needed without chasing anyone down. An SBOM (Software Bill of Materials) lists every package and dependency in your software supply chain — the same standard used across the software industry. An AI-BOM extends that same idea to AI-specific artifacts: models, datasets, and their versions, licenses, and provenance. AI Workspaces generates both automatically, so you get one auditable record of everything running — code, models, and data alike.