Figure Eight

What is Figure Eight?

Figure Eight is a company within the Artificial Intelligence Software category. Figure Eight (formerly CrowdFlower) is a specialist data labeling and annotation platform that enables machine learning teams to generate high-quality training data through human-in-the-loop workflows. Since its 2019 acquisition by Appen, its technology has been integrated into the Appen Data Annotation Platform.

When was Figure Eight founded and where is it based?

Figure Eight was founded in 2007 and is headquartered in San Francisco, CA (Legacy).

What is Figure Eight's Brand Authority Index tier?

Figure Eight is rated Leader on the Optimly Brand Authority Index, a measure of how well AI models can accurately describe the brand. The exact score is locked for unclaimed profiles.

How accurately do AI models describe Figure Eight?

AI narrative accuracy for Figure Eight is Strong. Significant factual deltas detected.

How do AI models position Figure Eight competitively?

AI models classify Figure Eight as a Misread. Visible but inaccurate.

How visible is Figure Eight in buyer-intent AI queries?

Figure Eight appeared in 5 of 8 sampled buyer-intent queries (63%). The biggest gap is the lack of current unbranded visibility; for most 'best of' queries, AI now prioritizes newer incumbents like Scale AI and Labelbox, or mentions the parent company Appen.

What do AI models currently say about Figure Eight?

AI reliably captures the historical trajectory of Figure Eight from its CrowdFlower origins to its acquisition. However, it often fails to clarify that Figure Eight no longer exists as a primary independent brand, frequently conflating it with Appen's broader service offerings. Key gap: The primary gap is the "frozen-in-time" nature of descriptions, often focusing on Figure Eight as a standalone company rather than a deprecated sub-brand of Appen.

How many facts about Figure Eight are well-documented vs need fixing vs retrieval-dependent?

Of 5 key facts verified about Figure Eight, 4 are well-documented (likely accurate across AI models), 1 have limited sourcing, and 0 are retrieval-dependent and may be inaccurate without live search.

What is Figure Eight's biggest AI narrative vulnerability?

Misrepresenting the current availability of the standalone Figure Eight platform vs. integrated Appen solutions.

What problems does Figure Eight solve for buyers?

Buyers turn to Figure Eight for Internal Tooling (Label Studio/CVAT): Building internal labeling teams and using open-source tools like Label Studio or CVAT., Traditional BPO/Outsourcing Firms: Engaging specialized BPO firms that provide human-in-the-loop services without a dedicated software platform., Low-Quality Data Maintenance: Maintaining the status quo with unorganized or poor quality training data, leading to failed AI deployments., among 3 documented problem areas.

What questions do buyers ask AI about Figure Eight?

Buyers evaluating Figure Eight typically ask AI models about "best data labeling platforms for computer vision", "human in the loop machine learning services", "RLHF platforms for LLM training", and 2 similar queries.

Who are Figure Eight's main competitors?

Figure Eight's main competitors are Amazon Sagemaker Ground Truth, Cloudfactory, Labelbox. According to AI models, these are the brands most frequently named alongside Figure Eight in buyer-intent queries.

What does Figure Eight offer?

Figure Eight's core products are Data Labeling Platform, Computer Vision Annotation, Sentiment Analysis, Text Categorization.

How is Figure Eight priced?

Figure Eight uses Enterprise/Custom.

Who does Figure Eight target?

Figure Eight serves Enterprise AI/ML teams, Search Engines, Autonomous Vehicle developers.

What differentiates Figure Eight from competitors?

Figure Eight One of the first platforms to combine automated quality control with a global crowd-sourced workforce for ML data.

Verified from Figure Eight website

Founded: 2007 (as CrowdFlower)

Headquarters: San Francisco, CA (Historical) / Sydney, Australia (Parent)

Competitors

• Amazon Sagemaker Ground Truth
• Cloudfactory
• Labelbox
• Scale AI

Problems this brand solves

• Internal Tooling (Label Studio/CVAT): Building internal labeling teams and using open-source tools like Label Studio or CVAT.
• Traditional BPO/Outsourcing Firms: Engaging specialized BPO firms that provide human-in-the-loop services without a dedicated software platform.
• Low-Quality Data Maintenance: Maintaining the status quo with unorganized or poor quality training data, leading to failed AI deployments.

Buyers search for

• best data labeling platforms for computer vision
• human in the loop machine learning services
• RLHF platforms for LLM training
• who acquired crowdflower
• enterprise training data solutions