Data Labeling Market: Research Snapshot Dec. 2021

Data Labeling Market: Research Snapshot Dec. 2021

In order for machine learning systems to be able to create accurate generalizations, they must be trained on data. Advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. Customers often don’t have the resources to label large data sets, nor do they have a mechanism to ensure accuracy and quality of data labeling. Labeling projects involve multiple steps as well as requiring human subjective decision making. Third party managed labeling solution providers and an increasing rate of data labeling tools address this gap by providing the labor to do the labeling combined with tools & expertise in large-scale data labeling efforts and an infrastructure for managing labeling workloads and achieving desired quality levels. In this latest snapshot of Cognilytica Market Intelligence, Cognilytica evaluates data labeling solutions across key market segments that provide needed annotations for machine learning training.

In this Research Snapshot of Cognilytica’s Market intelligence, we cover:

  • The Data Labeling Market Overview
  • Data Labeling market segments:
    • Crowdsourced Data Labeling
    • Managed Labeling Services
    • Full Service Data Labeling Solutions
    • Labeling Tools & Software
    • Synthetic Data Labeling
  • Data Labeling Market Forecasts and Trends across all market segments
  • Data Labeling Vendor Profiles covering 133 vendors with detailed profiles on “established” vendors
  • Decision Factors for Buyers of Data Labeling Solutions
  • Guided Questions to help Buyers interact with Data Labeling vendors

$3,495.00

Add to cart

Document Details
In order for machine learning systems to be able to create accurate generalizations, they must be trained on data. Advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. Customers often don’t have the resources to label large data sets, nor do they have a mechanism to ensure accuracy and quality of data labeling. Labeling projects involve multiple steps as well as requiring human subjective decision making. Third party managed labeling solution providers and an increasing rate of data labeling tools address this gap by providing the labor to do the labeling combined with tools & expertise in large-scale data labeling efforts and an infrastructure for managing labeling workloads and achieving desired quality levels. In this latest snapshot of Cognilytica Market Intelligence, Cognilytica evaluates data labeling solutions across key market segments that provide needed annotations for machine learning training.
  • The markets for Data Labeling solutions include the market segments of Crowdsourced Data Labeling, Managed Data Labeling Services Labor, Full Service “Turn-Key” Labeling Solutions, Labeling Tools & Software, and Synthetic Data Labeling.
  • The vendor landscape for Data Labeling continues to expand at a remarkable rate, with 133 vendors tracked in this research snapshot, representing growth of over 100 vendors since the last snapshot.
  • The market for data labeling solutions is over $4.18B in 2021 growing to $21.98B by end of 2027.
  • The Managed Data Labeling Services market segment is seeing the rapid entry of dozens to perhaps even hundreds of business process outsourcing (BPO) firms
  • The Data Labeling Tools and Software market segment is seeing rapid growth with 42 vendors.
  • The emerging Synthetic Data Labeling market segment is seeing the most rapid growth with expected 48% CAGR market growth.
  • The Full Service Data Labeling market segment is seeing robust 44% CAGR and is being increasingly dominated by well-funded high growth startups and is seeing increasing acquisition activity.
  • By 2027, over 50% of current labeling tasks will be automated or performed by AI systems.
  • Decision Factors and Guided Questions hinge around determination of labor needs, automated or AI-enabled labeling, required domain-expertise, geographic labor location, and data labeling specifics.
Snapshot Meta: Premium PDF. Source: Copyright © Cognilytica LLC
  • 87 Pages
  • 133 Vendors
  • 14 tables
  • 88 charts / graphs
  • 23 images
Table of Contents:
Executive Summary 5
Key Findings 5
Data Labeling Market Overview 6
“Ground Truth” Human-enabled Labeling 7
Data Labeling and Annotation Needs 7
Image Labeling and Annotation 7
Delineating portions of an image 7
Segmenting Images into separate components 8
Classifying images and applying metadata 8
Instance Segmentation (“Counting and Grouping”) 9
Image Keypoints & Landmarks 9
Video Labeling and Annotation 9
Image Specific Annotations: Frame-based vs. Continuous 9
Object tracking 10
Scenario, Gesture, & Action Classification 10
Text Labeling and Annotation 11
Entity annotation and keyphrase tagging 11
Parts of Speech identification 12
Text Classification 12
Sentiment and Intent 12
Entity Linking & Relationships 13
Text Sequences and Spans (Multi-Turn Conversations) 13
Character and handwriting recognition 14
Audio Labeling and Annotation 14
Audio Classification and Annotation 14
Speech Transcription and Audio Timestamping 14
Speaker Identification 15
“Sensor Fusion” and Point Cloud Labeling and Annotation 15
3D Object Segmentation & Distance Estimation 15
3D Object Classification 16
3D Point Cloud Cuboids 16
Structured Data Labeling 17
Multiple Row and Multiple Source Data Classification 17
Data Annotation and Labeling Use Cases 17
Synthetic Data and Data Labeling 18
Cognilytica Classification 20
About the Cognilytica Vendor Classification System 20
Data Labeling Market Segments 20
Crowdsourced Data Labeling 20
Managed Labeling Services (Managed Labor) 21
“Turn Key” Full Service Data Labeling 21
Data Labeling Tools & Software Platforms 21
Synthetic Data Labeling 21
Data Labeling Market Map Category Definitions 22
Labeling Labor 22
Crowdsourced Data Labeling 22
Managed Labeling Services (Managed Labor) 22
Labeling Platforms 22
“Turn Key” Full Service Data Labeling 22
Data Labeling Tools & Software Platforms 23
Labeling Data Generation 23
Synthetic Data Labeling 23
Data Labeling Market Forecast 24
Market Observations 25
Crowdsourced Data Labeling market segment 25
Managed Labeling Services (Managed Labor) market segment 25
“Turn Key” Full Service Data Labeling market segment 25
Labeling Tools and Software market segment 25
Synthetic Data market segment 25
Vendor Analysis 26
Use of Automation and Machine Learning in Data Labeling 28
Data Labeling Market Trends 29
Rapid Growth of Market and Vendor Entrants 29
Market Pressure on Full Service Providers 29
Diminishing Use of Crowdsourced Labor as % of Total Market 29
Rapid Growth of Synthetic Data Labeling Segment 29
Data Labeling Market Map & Key Vendor Profiles 30
Criteria for Determining Established and Emerging Vendors 30
Vendor Profiles in this Snapshot and Online 30
Crowdsourced Data Labeling Market Map & Vendor Profiles 31
Established Crowdsourced Data Labeling Vendor Profiles 31
Amazon Mechanical Turk (AWS) 31
ClickWorker 32
Emerging Crowdsourced Data Labeling Vendors Overview 33
Managed Labeling Services Market Map & Vendor Profiles 34
Established Managed Labeling Services Vendor Profiles 35
Welocalize 35
Emerging Managed Labeling Services Vendors Overview 36
Full Service Data Labeling Market Map & Vendor Profiles 40
Established Full Service Data Labeling Vendor Profiles 41
Alegion 41
Amazon SageMaker Ground Truth Plus 42
Appen 43
Clarifai 44
CloudFactory 45
Defined.AI 46
Hive 47
iMerit 48
Kili Technology 49
Labelbox 50
Sama (formerly Samasource) 51
Scale AI 52
TaskUs 53
Telus International (including Lionbridge and Playment) 54
Transperfect DataForce 55
Emerging Full Service Data Labeling Vendors Overview 56
Labeling Tools and Software Market Map & Vendor Profiles 58
Established Labeling Tools and Software Vendor Profiles 59
Chooch 59
Dataloop 60
Deepomatic 61
Google Cloud AI Training Data Services (Vertex AI) 62
Mathworks (Labeler Apps) 63
Roboflow 64
Snorkel AI 65
Super.AI 66
SuperAnnotate 67
Superb AI 68
Emerging Labeling Tools and Software Vendors Overview 69
Open Source Labeling Tools and Software Overview 71
Synthetic Data Market Map & Vendor Profiles 72
Established and Emerging Synthetic Data Vendor Profiles 72
Data Labeling: Decision Factors 73
Data Labeling Solution Provider Considerations 73
Location Agnostic vs. Location-Specific Labor Pools 73
Customer-Managed vs. Third-Party Managed Labor Pools 73
Generic vs. Domain-Specific Labor Pools 74
Single Vendor for Labeling Solution vs. Multiple Labeling Provers vs. Internal Labeling 74
Labeling Tools vs. Labor Providers 75
Crowdsourced vs. Managed Labor Pool 75
Managed Labeling Services vs “Full Service” 75
Cloud vs. On-Premise 76
Labeling as Primary Vendor Offering vs. Labeling as One of Many Vendor Offerings 76
Data Engineering Needs 76
Data Labeling Solution Vendor Requirements 76
Decision Factors to Guide Vendor Selection 77
Data Labeling: Guided Questions 81
Questions for Vendors on Data Engineering & Generation Capabilities 82
Questions for Vendors on Image Labeling Capabilities 82
Questions for Vendors on Video Labeling Capabilities 83
Questions for Vendors on Text Labeling Capabilities 83
Questions for Vendors on Audio Labeling Capabilities 84
Questions for Vendors on Sensor Fusion & Point Cloud Labeling Capabilities 84
Questions for Vendors on Structured Data Labeling Capabilities 85
Questions for Labeling Tool Vendors 85
Questions for Vendors on Automation of Labeling Capabilities 85
Questions for Vendors on Quality Assurance of Data Labeling 85
Questions for Vendors on Labor Pool Considerations 85
Questions for Vendors on Pricing and Support 86
Related Research 87
About Cognilytica 87