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Synopsis
In-house data labeling refers to the process of assigning labels or annotations to data within an organization, typically for the purpose of training machine learning models. It involves manually reviewing and categorizing data according to predefined criteria or guidelines.
Global In-house Data Labeling market is projected to reach US$ million in 2029, increasing from US$ million in 2022, with the CAGR of % during the period of 2023 to 2029. Influencing issues, such as economy environments, COVID-19 and Russia-Ukraine War, have led to great market fluctuations in the past few years and are considered comprehensively in the whole In-house Data Labeling market research.
Key companies engaged in the In-house Data Labeling industry include Alegion, Amazon Mechanical Turk, Inc., Appen Limited, Clickworker GmbH, CloudFactory Limited, Cogito Tech LLC, Deep Systems, LLC, edgecase.ai and Explosion AI GmbH, etc. Among those companies, the top 3 players guaranteed % supply worldwide in 2022.
When refers to consumption region, % value of In-house Data Labeling were sold to North America, Europe and Asia Pacific in 2022. Moreover, China, plays a key role in the whole In-house Data Labeling market and estimated to attract more attentions from industry insiders and investors.
Report Scope
This report, based on historical analysis (2018-2022) and forecast calculation (2023-2029), aims to help readers to get a comprehensive understanding of global In-house Data Labeling market with multiple angles, which provides sufficient supports to readers’ strategy and decision making.
By Company
- Alegion
- Amazon Mechanical Turk, Inc.
- Appen Limited
- Clickworker GmbH
- CloudFactory Limited
- Cogito Tech LLC
- Deep Systems, LLC
- edgecase.ai
- Explosion AI GmbH
- Labelbox, Inc
- Mighty AI, Inc.
- Playment Inc.
- Scale AI
- Tagtog Sp. z o.o.
- Trilldata Technologies Pvt Ltd
Segment by Type
- Manual
- Semi-Supervised
- Automatic
Segment by Application
- Automotive
- Healthcare
- Financial Services
- Retails
- Others
By Region
- North America (United States, Canada)
- Europe (Germany, France, U.K., Italy, Russia, Nordic Countries, Rest of Europe)
- Asia-Pacific (China, Japan, South Korea,Southeast Asia, India, Australia, Rest of Asia)
- Latin America (Mexico, Brazil, Rest of Latin America)
- Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of MEA)
The In-house Data Labeling report covers below items:
Chapter 1: Product Basic Information (Definition, Type and Application)
Chapter 2: Global market size, regional market size. Market Opportunities and Challenges
Chapter 3: Companies’ Competition Patterns
Chapter 4: Product Type Analysis
Chapter 5: Product Application Analysis
Chapter 6 to 10: Country Level Value Analysis
Chapter 11: Companies’ Outline
Chapter 12: Market Conclusions
Chapter 13: Research Methodology and Data Source
Index
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global In-house Data Labeling Market Size Growth Rate by Type: 2018 VS 2022 VS 2029
1.2.2 Manual
1.2.3 Semi-Supervised
1.2.4 Automatic
1.3 Market by Application
1.3.1 Global In-house Data Labeling Market Growth by Application: 2018 VS 2022 VS 2029
1.3.2 Automotive
1.3.3 Healthcare
1.3.4 Financial Services
1.3.5 Retails
1.3.6 Others
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global In-house Data Labeling Market Perspective (2018-2029)
2.2 In-house Data Labeling Growth Trends by Region
2.2.1 Global In-house Data Labeling Market Size by Region: 2018 VS 2022 VS 2029
2.2.2 In-house Data Labeling Historic Market Size by Region (2018-2023)
2.2.3 In-house Data Labeling Forecasted Market Size by Region (2024-2029)
2.3 In-house Data Labeling Market Dynamics
2.3.1 In-house Data Labeling Industry Trends
2.3.2 In-house Data Labeling Market Drivers
2.3.3 In-house Data Labeling Market Challenges
2.3.4 In-house Data Labeling Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top In-house Data Labeling Players by Revenue
3.1.1 Global Top In-house Data Labeling Players by Revenue (2018-2023)
3.1.2 Global In-house Data Labeling Revenue Market Share by Players (2018-2023)
3.2 Global In-house Data Labeling Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by In-house Data Labeling Revenue
3.4 Global In-house Data Labeling Market Concentration Ratio
3.4.1 Global In-house Data Labeling Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by In-house Data Labeling Revenue in 2022
3.5 In-house Data Labeling Key Players Head office and Area Served
3.6 Key Players In-house Data Labeling Product Solution and Service
3.7 Date of Enter into In-house Data Labeling Market
3.8 Mergers & Acquisitions, Expansion Plans
4 In-house Data Labeling Breakdown Data by Type
4.1 Global In-house Data Labeling Historic Market Size by Type (2018-2023)
4.2 Global In-house Data Labeling Forecasted Market Size by Type (2024-2029)
5 In-house Data Labeling Breakdown Data by Application
5.1 Global In-house Data Labeling Historic Market Size by Application (2018-2023)
5.2 Global In-house Data Labeling Forecasted Market Size by Application (2024-2029)
6 North America
6.1 North America In-house Data Labeling Market Size (2018-2029)
6.2 North America In-house Data Labeling Market Growth Rate by Country: 2018 VS 2022 VS 2029
6.3 North America In-house Data Labeling Market Size by Country (2018-2023)
6.4 North America In-house Data Labeling Market Size by Country (2024-2029)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe In-house Data Labeling Market Size (2018-2029)
7.2 Europe In-house Data Labeling Market Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 Europe In-house Data Labeling Market Size by Country (2018-2023)
7.4 Europe In-house Data Labeling Market Size by Country (2024-2029)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific In-house Data Labeling Market Size (2018-2029)
8.2 Asia-Pacific In-house Data Labeling Market Growth Rate by Region: 2018 VS 2022 VS 2029
8.3 Asia-Pacific In-house Data Labeling Market Size by Region (2018-2023)
8.4 Asia-Pacific In-house Data Labeling Market Size by Region (2024-2029)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America In-house Data Labeling Market Size (2018-2029)
9.2 Latin America In-house Data Labeling Market Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Latin America In-house Data Labeling Market Size by Country (2018-2023)
9.4 Latin America In-house Data Labeling Market Size by Country (2024-2029)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa In-house Data Labeling Market Size (2018-2029)
10.2 Middle East & Africa In-house Data Labeling Market Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Middle East & Africa In-house Data Labeling Market Size by Country (2018-2023)
10.4 Middle East & Africa In-house Data Labeling Market Size by Country (2024-2029)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Alegion
11.1.1 Alegion Company Detail
11.1.2 Alegion Business Overview
11.1.3 Alegion In-house Data Labeling Introduction
11.1.4 Alegion Revenue in In-house Data Labeling Business (2018-2023)
11.1.5 Alegion Recent Development
11.2 Amazon Mechanical Turk, Inc.
11.2.1 Amazon Mechanical Turk, Inc. Company Detail
11.2.2 Amazon Mechanical Turk, Inc. Business Overview
11.2.3 Amazon Mechanical Turk, Inc. In-house Data Labeling Introduction
11.2.4 Amazon Mechanical Turk, Inc. Revenue in In-house Data Labeling Business (2018-2023)
11.2.5 Amazon Mechanical Turk, Inc. Recent Development
11.3 Appen Limited
11.3.1 Appen Limited Company Detail
11.3.2 Appen Limited Business Overview
11.3.3 Appen Limited In-house Data Labeling Introduction
11.3.4 Appen Limited Revenue in In-house Data Labeling Business (2018-2023)
11.3.5 Appen Limited Recent Development
11.4 Clickworker GmbH
11.4.1 Clickworker GmbH Company Detail
11.4.2 Clickworker GmbH Business Overview
11.4.3 Clickworker GmbH In-house Data Labeling Introduction
11.4.4 Clickworker GmbH Revenue in In-house Data Labeling Business (2018-2023)
11.4.5 Clickworker GmbH Recent Development
11.5 CloudFactory Limited
11.5.1 CloudFactory Limited Company Detail
11.5.2 CloudFactory Limited Business Overview
11.5.3 CloudFactory Limited In-house Data Labeling Introduction
11.5.4 CloudFactory Limited Revenue in In-house Data Labeling Business (2018-2023)
11.5.5 CloudFactory Limited Recent Development
11.6 Cogito Tech LLC
11.6.1 Cogito Tech LLC Company Detail
11.6.2 Cogito Tech LLC Business Overview
11.6.3 Cogito Tech LLC In-house Data Labeling Introduction
11.6.4 Cogito Tech LLC Revenue in In-house Data Labeling Business (2018-2023)
11.6.5 Cogito Tech LLC Recent Development
11.7 Deep Systems, LLC
11.7.1 Deep Systems, LLC Company Detail
11.7.2 Deep Systems, LLC Business Overview
11.7.3 Deep Systems, LLC In-house Data Labeling Introduction
11.7.4 Deep Systems, LLC Revenue in In-house Data Labeling Business (2018-2023)
11.7.5 Deep Systems, LLC Recent Development
11.8 edgecase.ai
11.8.1 edgecase.ai Company Detail
11.8.2 edgecase.ai Business Overview
11.8.3 edgecase.ai In-house Data Labeling Introduction
11.8.4 edgecase.ai Revenue in In-house Data Labeling Business (2018-2023)
11.8.5 edgecase.ai Recent Development
11.9 Explosion AI GmbH
11.9.1 Explosion AI GmbH Company Detail
11.9.2 Explosion AI GmbH Business Overview
11.9.3 Explosion AI GmbH In-house Data Labeling Introduction
11.9.4 Explosion AI GmbH Revenue in In-house Data Labeling Business (2018-2023)
11.9.5 Explosion AI GmbH Recent Development
11.10 Labelbox, Inc
11.10.1 Labelbox, Inc Company Detail
11.10.2 Labelbox, Inc Business Overview
11.10.3 Labelbox, Inc In-house Data Labeling Introduction
11.10.4 Labelbox, Inc Revenue in In-house Data Labeling Business (2018-2023)
11.10.5 Labelbox, Inc Recent Development
11.11 Mighty AI, Inc.
11.11.1 Mighty AI, Inc. Company Detail
11.11.2 Mighty AI, Inc. Business Overview
11.11.3 Mighty AI, Inc. In-house Data Labeling Introduction
11.11.4 Mighty AI, Inc. Revenue in In-house Data Labeling Business (2018-2023)
11.11.5 Mighty AI, Inc. Recent Development
11.12 Playment Inc.
11.12.1 Playment Inc. Company Detail
11.12.2 Playment Inc. Business Overview
11.12.3 Playment Inc. In-house Data Labeling Introduction
11.12.4 Playment Inc. Revenue in In-house Data Labeling Business (2018-2023)
11.12.5 Playment Inc. Recent Development
11.13 Scale AI
11.13.1 Scale AI Company Detail
11.13.2 Scale AI Business Overview
11.13.3 Scale AI In-house Data Labeling Introduction
11.13.4 Scale AI Revenue in In-house Data Labeling Business (2018-2023)
11.13.5 Scale AI Recent Development
11.14 Tagtog Sp. z o.o.
11.14.1 Tagtog Sp. z o.o. Company Detail
11.14.2 Tagtog Sp. z o.o. Business Overview
11.14.3 Tagtog Sp. z o.o. In-house Data Labeling Introduction
11.14.4 Tagtog Sp. z o.o. Revenue in In-house Data Labeling Business (2018-2023)
11.14.5 Tagtog Sp. z o.o. Recent Development
11.15 Trilldata Technologies Pvt Ltd
11.15.1 Trilldata Technologies Pvt Ltd Company Detail
11.15.2 Trilldata Technologies Pvt Ltd Business Overview
11.15.3 Trilldata Technologies Pvt Ltd In-house Data Labeling Introduction
11.15.4 Trilldata Technologies Pvt Ltd Revenue in In-house Data Labeling Business (2018-2023)
11.15.5 Trilldata Technologies Pvt Ltd Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Published By : QY Research
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