Atlan vs Weights and Biases

By valuation, Weights and Biases is the larger company at $1.3B versus $750M — a 1.7x difference. Size can also be measured by team: Atlan employs 200-500 people while Weights and Biases has 300 employees.

Weights and Biases has raised more in total funding at $250M, compared to Atlan's $206M — a gap of $44M. Combined, the two companies have completed 7 known funding rounds.

Weights and Biases leads with an Awaira Score of 80/100, while Atlan sits at 68/100. That 12-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Atlan was founded by Prukalpa Sankar in 2018. Weights and Biases was founded by Lukas Biewald in 2017. Visit each company's profile on Awaira for a full founder biography.

Atlan: Atlan is an active metadata platform and data workspace that enables data teams to discover, understand, and govern data assets across cloud warehouses, lakes, BI tools, and pipelines through an AI-powered catalog interface. The platform automatically crawls data infrastructure to build lineage graphs, enables natural language search over data assets, and enforces data governance policies through automated tagging and access controls.\n\nThe company raised approximately $78M in Series C funding from investors including Insight Partners and Sequoia India, and has built a global customer base of data-forward technology companies and enterprises. Atlan has emerged as a recognized leader in the data catalog market, competing with Alation, Collibra, and DataHub in the modern data stack ecosystem.\n\nAs cloud data infrastructure has proliferated, data discoverability and governance have become critical operational problems for engineering teams managing hundreds of data sources. Atlan's modern metadata-first approach and deep integrations with the contemporary data stack — Snowflake, dbt, Fivetran, Looker — position it well in a market where legacy catalog vendors have struggled to keep pace with infrastructure evolution. Weights and Biases: Weights and Biases is a machine learning platform founded in 2017 that provides infrastructure for experiment tracking, model management, and collaboration in AI development. The company's core product enables data scientists and ML engineers to log, visualize, and compare machine learning experiments, addressing the reproducibility and collaboration challenges inherent in modern AI workflows. The platform integrates with popular ML frameworks including PyTorch, TensorFlow, and scikit-learn, allowing teams to track metrics, parameters, and outputs across training runs. W&B's offering extends to model registry capabilities, enabling organizations to version, document, and deploy models systematically. The company serves enterprises across computer vision, natural language processing, and reinforcement learning domains. As of its Series C funding stage, Weights and Biases has raised $250 million at a $1.3 billion valuation, positioning it among well-capitalized AI infrastructure startups. The company competes in the ML operations space alongside platforms like Databricks and Neptune, differentiating through its focus on experiment tracking and accessibility to individual practitioners and teams. Notable adoption spans research institutions and technology companies implementing large-scale ML pipelines. The platform's freemium model has facilitated rapid adoption within the academic and startup ecosystems, while enterprise offerings target organizations requiring advanced governance and integration capabilities. Growth trajectory reflects increasing enterprise demand for ML operations infrastructure. Weights and Biases occupies a critical position in the ML operations stack by specializing in experiment tracking and model management, essential infrastructure that bridges individual data scientist workflows and enterprise-scale ML deployment.

Weights and Biases got there first, launching in 2017 — that's 1 year of extra runway. Atlan didn't arrive until 2018. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Atlan has about 200-500 employees; Weights and Biases has about 300. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Atlan and Weights and Biases compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.