Startups > Anaconda

Anaconda

Anaconda helps enterprises build and govern AI systems on open-source Python.

Series C $210M total Founded 2012 Austin, Texas 544 employees

Anaconda provides a secure, governed platform for open-source Python package management and AI development across the entire lifecycle. The company offers Conda, a dependency and environment manager that ensures reproducibility and compatibility across platforms, solving critical challenges with unvetted packages, dependency conflicts, and security gaps. Trusted by 95% of Fortune 500 companies and 50 million users globally, Anaconda enables enterprises to build and deploy AI systems reliably while maintaining governance and compliance.

Problem solved

Enterprise teams struggle to reliably manage open-source dependencies, ensure environment reproducibility, maintain security governance, and scale AI development across teams without breaking builds or creating security vulnerabilities.

Target customer

Enterprise data science and AI teams, Fortune 500 companies with 200+ employees, organizations building AI/ML systems at scale

Website LinkedIn Crunchbase Twitter / X

Founders

Peter Wang

Co-Founder

15 years in software design across 3D graphics, geophysics, data simulation, financial modeling, and medical imaging; creator of PyData community; BA in Physics from Cornell University.

Travis Oliphant

Co-Founder

Co-founder who identified the opportunity to make Python mainstream in data science and analytics.

Funding history

Seed $2.6M 2012 Led by Unknown · Unknown

DARPA Funding Unknown 2013 Led by DARPA · Unknown

Series A $24M 2015 Led by General Catalyst · BuildGroup

Series B Unknown 2018-2021 Led by Multiple · Snowflake, Citi Ventures

Series B Extension $30M 2021 Led by Unknown · Unknown

Series C $150M July 31, 2025 Led by Insight Partners · Mubadala Capital

Total raised: $210M

Industries

Artificial Intelligence (AI) Analytics Big Data Cloud Infrastructure Enterprise Software Machine Learning Open Source

Pricing

Tiered model: Free ($0), Starter ($15/month per user), Business ($50/month per user), Enterprise (custom). Organizations with 200+ employees/contractors must use paid Business or Enterprise licenses.

Notable customers

95% of Fortune 500 including Panasonic, AmTrust, Booz Allen Hamilton; 50 million total users; 21+ billion package downloads

Tech stack

GSAP (JavaScript frameworks) jQuery (JavaScript libraries) core-js (JavaScript libraries) parcel DocuSign Zoominfo (Analytics) VWO (Analytics) Linkedin Insight Tag (Analytics) Hotjar (Analytics) Heap (Analytics) Google Analytics (Analytics) Google Ads Conversion Tracking (Analytics) Facebook Pixel (Analytics) Cloudflare Bot Management (Security) reCAPTCHA (Security) Typekit (Font scripts) Google Workspace (Email) Cloudflare (CDN) Marketo (Marketing automation) theTradeDesk (Advertising) Google Tag Manager (Tag managers)

Website

anaconda.com/

Competitors

Databricks

Broader end-to-end data and AI platform with recent $1.8B funding; Anaconda focuses specifically on Python package management and governance.

Altair

Specializes in data visualization and analytics; lacks Anaconda's focus on package management and dependency resolution.

C3 AI

Enterprise AI platform focused on applications; Anaconda is the foundation layer for open-source development and deployment.

Why this matters: Anaconda owns the Python data science ecosystem with 21+ billion downloads and is trusted by nearly all Fortune 500 companies, making it a critical infrastructure layer for enterprise AI. The recent $150M Series C in July 2025 from Insight Partners validates the company's growing importance as enterprises scale AI systems and require governance, security, and reproducibility that open-source alone cannot provide.

Best for: Enterprise data science and ML teams that need reliable, reproducible, secure open-source Python environments at scale across multiple deployments.

Use cases

Enterprise AI Model Deployment

Large organizations use Anaconda to ensure AI models developed locally run identically in production, eliminating environment drift and dependency conflicts. Teams can enforce security policies and version controls across all deployments while maintaining compliance requirements.

Cross-Team Data Science Collaboration

Data science teams working on shared projects use Conda to synchronize environments, ensuring everyone works with the same package versions and dependencies. This eliminates 'works on my machine' problems and reduces troubleshooting time dramatically.

Secure Open-Source Governance

Enterprises use Anaconda's governed platform to curate and vet open-source packages before teams use them, maintaining security and compliance standards without blocking innovation. Custom hosting options allow on-premises or private cloud deployment for regulated industries.

Alternatives

pip + virtualenv Basic Python package management without the cross-platform compatibility, binary package support, or enterprise governance features Anaconda provides.

Poetry Lighter-weight dependency management focused on application development; lacks Anaconda's data science focus and enterprise governance capabilities.

Mamba Faster implementation of Conda's package manager but doesn't provide the enterprise governance, security, and platform features of Anaconda.

FAQ

What does Anaconda do? +

Anaconda provides a secure, governed platform for managing open-source Python packages, environments, and dependencies for AI and data science development. It ensures reproducibility across platforms, maintains security governance, and scales reliably from development to production. The platform is used by 95% of Fortune 500 companies and 50 million users globally.

How much does Anaconda cost? +

Anaconda offers Free ($0), Starter ($15/month per user), Business ($50/month per user), and Enterprise (custom pricing) tiers. Organizations with 200+ employees require a paid Business or Enterprise license.

What are alternatives to Anaconda? +

Alternatives include Databricks (broader data/AI platform), Poetry (lightweight dependency management), Mamba (faster package manager), and traditional pip + virtualenv (basic Python package management). Each lacks Anaconda's specific combination of cross-platform compatibility, data science focus, and enterprise governance.

Who uses Anaconda? +

Anaconda is used by 95% of Fortune 500 companies including Panasonic, AmTrust, and Booz Allen Hamilton. The target customers are enterprise data science teams, organizations building AI/ML systems at scale, and companies requiring secure, governed open-source management across 200+ employees.

How does Anaconda compare to Databricks? +

Databricks is a broader end-to-end data and AI platform with recent $1.8B funding, while Anaconda focuses specifically on Python package management, dependency resolution, and governance. Anaconda excels as a foundation layer for open-source development, while Databricks provides more comprehensive data engineering and ML features.