Open Source Security: Risks, Benefits, and Best Practices
Open source is the foundation of modern software. Studies show that 96% of enterprise software applications include open source components, and 70–90% of every codebase consists of open source modules. Anaconda’s research illustrates that reality, too: 91% of IT workers report using open source software in their current workflow. That ubiquity brings transparency, rapid innovation, […]
AI in Banking: How Financial Institutions Are Scaling Intelligent Systems
The banking industry has been a pioneer and proving ground for enterprise AI. Even before other sectors experimented with pilots, financial institutions moved AI from proof of concept to production at scale. This shift has happened over the past decade, as banking’s data-rich environment, regulatory requirements, and competitive pressures pushed the industry to adopt AI […]
The Python Packages You Didn’t Install Are Now Your Biggest Security Risk
It’s been a brutal two weeks for the open source supply chain. On March 19, the Trivy vulnerability scanner, the tool many teams rely on to detect supply chain attacks, was itself compromised (oh, the irony). Five days later, a cascading effect from the Trivy breach led directly to the compromise of LiteLLM, one of […]
Secure by Default
SECURE BY DEFAULT Deploy AI With Confidence Every package, model, and dependency is scanned, verified, and governed before your teams ever use it in production. Security isn’t a gate at the end of the workflow—it’s built into every step. Request a Demo THE CHALLENGE Security Risk Scales Faster Than Most Teams Can Keep Up Every […]
Dependency Hell in AI: Why ML Package Conflicts Are a Governance Problem
The Problem That Looks Like a Tuesday It usually starts with a help desk ticket or a Slack message that says something like: “The model we deployed last month is throwing errors in production.” An engineer digs in. The culprit is not the model itself. It is a transitive dependency—a package that another package requires—that […]
AI Governance: Best Practices, Frameworks, and Implementation
In March 2024, while running routine benchmarks, Microsoft developer Andres Freund noticed SSH logins were running a half-second slower than they should. He described it as a “weird symptom” and started poking around. What he found instead was a malicious backdoor that could have compromised nearly every server on the internet. The attack was more […]
How to Govern Open Source AI at Scale
Govern open source AI models without slowing innovation Enterprise adoption of open source AI models is growing, with 43% of organizations planning to invest $1 million+ in AI initiatives. Yet 62% face challenges moving models into production due to governance issues like security, compliance, and licensing risks. This showcase explores how to leverage open source […]
Environment Maturity Assessment: Evaluate Your AI and Data Science Infrastructure
Use this assessment to evaluate the maturity of your organization’s environment management practices for AI and data science workflows. Instructions Complete the 8-question assessment below and calculate your total score. You’ll immediately see which maturity level your organization has reached, from Survival Mode to Optimizing. After calculating your score, enter your information to download a […]
Developer Hub
Developer Resources Developer Hub Build AI that Scales The Foundation for AI and Data Science GET STARTED Set Up Your Environment Get started with conda through our interactive tutorial on environments and package management. Start Now ANACONDA-TOOLS Anaconda Tools Explore Anaconda’s tools: desktop apps, cloud notebooks, package management, and AI development. See Tools What’s New […]
Data Modeling: Best Practices for Scalable Python Workflows
A customer churn model crashes in production when it encounters unexpected null values in a revenue field that never appeared in training data. The model performed beautifully in notebooks, but when deployed, the pipeline can’t handle the bad data. Features that worked locally fail in production, and team members can’t reproduce results. After days of […]