Appen vs Atlan

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Appen employs 1000+ people, while Atlan has 200-500 employees.

Atlan has raised $78M in disclosed funding across 0 known rounds. Appen's funding history is not publicly available.

Atlan holds the higher Awaira Score at 68/100, compared to Appen's 55/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 13-point gap that reflects meaningful differences in scale or traction.

Appen was founded by Mark Brayan in 1996. Atlan was founded by Prukalpa Sankar in 2018. Visit each company's profile on Awaira for a full founder biography.

Appen: Appen is an AI training data collection and annotation company that provides human-annotated datasets, relevance judgements, and content quality evaluation services used to train and evaluate AI models for search engines, voice assistants, autonomous vehicles, and generative AI systems. The Sydney company operates a global crowd workforce of over one million contractors who perform data annotation, transcription, translation, and content evaluation tasks under managed quality assurance processes.\n\nPublicly listed on the Australian Securities Exchange under ticker APX, Appen has historically generated revenue from long-term data services contracts with major US technology companies including Google, Meta, Amazon, and Microsoft. The company has faced significant revenue pressure as its largest clients have reduced external data annotation spending in favour of internal annotator teams and synthetic data generation, resulting in revenue declines and strategic restructuring since 2022.\n\nAppen competes in the AI data services market against Scale AI, Surge AI, and DataAnnotation, as well as crowdsourcing platforms including Amazon Mechanical Turk. The company faces structural challenges as generative AI and synthetic data approaches reduce demand for the human-annotated data that has historically been its primary product. Appen has been pursuing strategic alternatives including diversification into AI deployment services and government data contracts to offset declining technology company data annotation revenue, reflecting the broader market disruption facing traditional human annotation businesses. 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.

Appen was founded first in 1996, giving it 22 years of additional market experience. Atlan was founded later in 2018. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Appen has approximately 1000+ employees, while Atlan has approximately 200-500. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Appen and Atlan are direct competitors — both operate in the AI Data space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.