AI Buyer Insights:

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Michelin, an e2open customer evaluated Oracle Transportation Management

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Michelin, an e2open customer evaluated Oracle Transportation Management

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

List of Figure Eight Platform Customers

loading spinner icon



Apply Filters For Customers

Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Adobe Professional Services 31360 $23.8B United States Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
In 2016, Adobe deployed the Figure Eight Platform to create high-quality training data for Adobe Stock search and discovery. Adobe Stock contains over 120,000,000 photos, diagrams, videos, and graphics with roughly 150,000 new uploads each day, and Adobe required annotation at scale to surface nuanced image attributes that uploader metadata does not capture. The Figure Eight Platform was configured to run polygon annotation workflows and human-in-the-loop labeling tasks, enabling annotators to draw polygons over copy space and similar features and to mark object isolation characteristics. These functional capabilities produced curated, high-accuracy labeled datasets that informed computer vision model training, and the narrative explicitly references the Figure Eight Platform as the annotation engine. Annotated outputs were consumed by Adobe’s model training pipelines and applied to Adobe Stock search and discovery, extending coverage across the entire catalog and incoming daily uploads. The implementation impacted product search and content discovery functions and supported use cases for marketing customers who need images optimized for overlaid text and clean composition. Governance combined human labeling with existing automated metadata and color attribute extraction, using human-in-the-loop processes to complement rather than replace algorithmic signals. The result is models that better surface images with attributes like copy space and object isolation, enabling users to find highly useful assets more quickly and accelerate marketing content creation.
Blue River Technology Manufacturing 80 $17M United States Appen Figure Eight Platform ML and Data Science Platforms 2017 n/a
In 2017, Blue River Technology implemented the Figure Eight Platform as part of its ML and Data Science Platforms adoption to support high-fidelity labeling for its See & Spray product line. See & Spray augments self-propelled sprayers with on-board computing and vision algorithms to distinguish crops from weeds across large-scale farms, addressing the operational inefficiency of blanket herbicide application. The implementation targeted the core problem of costly and imprecise spraying, enabling per-plant decisioning in the spraying workflow. Blue River used the Figure Eight Platform to generate pixel by pixel labeled images, creating training datasets for its computer vision models. The platform supported annotation workflows that identified specific plant types such as cotton and pigweed, and those labeled datasets were consumed by Blue River’s model training pipeline. The Figure Eight Platform processed real-world field imagery supplied by Blue River to produce iterative datasets for model refinement. Operationally, imagery was routed from field-mounted cameras on See & Spray machines into the Figure Eight Platform, then the labeled outputs were ingested into Blue River’s model training and validation systems. Trained models were deployed to on-board computing units on the sprayers to perform real-time inference and precision actuation of spraying hardware. The solution connected field operations with engineering and data science functions across large-scale farm sites. The deployment established an iterative feedback loop where field teams continuously upload new images and Blue River expands label taxonomies to include new weed species, supporting frequent retraining cycles and dataset versioning. Governance centered on label taxonomy management and controlled model releases to shift operational procedures from blanket spraying to model-driven selective spraying. Processes were restructured to prioritize field data collection, annotation workflows, and operational integration of model outputs into actuation systems. Outcomes documented in the case include a reported 90% reduction in average herbicide spend and the enabling of non-GMO seed use that costs about half the price of treated seeds. The Figure Eight Platform enabled species level identification so sprayers can avoid applying ineffective herbicides on resistant weeds. Reduced herbicide usage was also noted for its environmental benefit, lowering chemical runoff into the water table.
CrowdReason, LLC Professional Services 10 $1M United States Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
In 2016, CrowdReason, LLC deployed the Figure Eight Platform as part of an effort to automate extraction from property tax forms across more than 20,000 U.S. taxing jurisdictions, leveraging ML and Data Science Platforms to scale document processing. The Figure Eight Platform was used to operationalize human-in-the-loop labeling and automated task routing alongside CrowdReason’s in-house OCR and feature extraction capabilities. Implementation centered on an OCR model that reads scanned documents and a fingerprinting module that characterizes a document by extracted features to determine prior occurrences. Documents identified as unseen are routed through the Figure Eight Platform where a series of human tasks extract multiple data points, and each extracted field feeds an extraction algorithm that optimizes bounding boxes and template definitions over time. The solution is integrated into CrowdReason’s core product workflow, with bots applying preloaded algorithms to make unstructured decisions and with human workers resolving low confidence items before aggregated results are delivered to the customer. Operational coverage focuses on document ingestion, feature fingerprinting, field extraction, and downstream delivery to tax processing workflows for CrowdReason customers managing multi-jurisdictional liabilities. Governance and workflow transformation emphasized iterative model training and confidence thresholds, moving from an initial 100 percent manual extraction process to a model where humans are required for less than 40 percent of data extraction. Over time the automated templates and bounding box performance improve so that more than 60 percent of scanned document data is extracted without human input, with the stated goal of ultimately recognizing and extracting data with no human intervention.
Retail 11500 $2.6B United States Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
Professional Services 10 $1M Hong Kong Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
Professional Services 9000 $1.0B Netherlands Appen Figure Eight Platform ML and Data Science Platforms 2017 n/a
Retail 470000 $159.5B United States Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
Media 9123 $3.2B Sweden Appen Figure Eight Platform ML and Data Science Platforms 2016 n/a
Showing 1 to 8 of 8 entries

Buyer Intent: Companies Evaluating Figure Eight Platform

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Figure Eight Platform. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Figure Eight Platform for ML and Data Science Platforms include:

  1. City of Barnesville, GA, a United States based Government organization with 50 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
No data found
FAQ - APPS RUN THE WORLD Figure Eight Platform Coverage

Figure Eight Platform is a ML and Data Science Platforms solution from Appen.

Companies worldwide use Figure Eight Platform, from small firms to large enterprises across 21+ industries.

Organizations such as Home Depot, Adobe, Spotify, eBay and Here Technologies are recorded users of Figure Eight Platform for ML and Data Science Platforms.

Companies using Figure Eight Platform are most concentrated in Retail, Professional Services and Media, with adoption spanning over 21 industries.

Companies using Figure Eight Platform are most concentrated in United States, Sweden and Netherlands, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Figure Eight Platform across Americas, EMEA, and APAC.

Companies using Figure Eight Platform range from small businesses with 0-100 employees - 37.5%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 25%, and global enterprises with 10,000+ employees - 37.5%.

Customers of Figure Eight Platform include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified Figure Eight Platform customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.