Appen Limited
Appen provides accurate and reliable human-annotated datasets that fuel AI and machine learning for some of the world's biggest brands, helping them achieve their AI goals through crowd solutions and expertise.
At a Glance
- Technology companies
- Automotive industry
- Retail and eCommerce
- Financial services
- +7 more
AI Tools by Appen Limited
(1)
Appen
AI Training Data Annotation Platform
Discussions
No discussions yet
Be the first to start a discussion about Appen Limited
Latest News
Notice of ceasing to be a substantial holder
Appen research identifies refusal as a safety strategy
Appen drives Agentic AI innovation with custom data and end-to-end evaluation
How Multimodal AI Will Spawn A New Wave Of Innovation
Products & Services
Appen's flexible AI data platform merges automation and human oversight to deliver high-quality data for a wide range of data modalities and AI use cases. It streamlines complex workflows, enabling fast model iterations and the development of advanced AI systems that align with user needs.
Comprehensive data collection, labeling, and annotation services for diverse data types to create training datasets for AI models. Includes text, image, audio, video, 3D point cloud, and 4D annotation capabilities.
Solutions for enterprises to customize Large Language Models with proprietary data and internal subject matter experts, including supervised fine-tuning and human preference scoring.
Enhanced LLM evaluation solutions for model development and assessment.
Market Position
Appen is a global leader in AI data annotation and training data services with over 25 years of industry experience. The company differentiates itself through its massive global crowd network of over 1 million contributors operating across 180 languages and 130 countries, enabling it to process more data more quickly than competitors. Appen powers many of the AI interactions experienced daily and serves eight of the top ten largest technology companies. Key competitors include Scale AI, Labelbox, and other data annotation platforms. Appen acquired Figure Eight in 2019, consolidating its position in the market. The company's broad capabilities span automatic speech recognition, computer vision, natural language processing, and multimodal AI. Appen is recognized as a leader in Everest Group's Data Annotation and Labeling Solutions for AI/ML PEAK Matrix Assessment 2024.
Leadership
Founders
Dr. Julie Vonwiller
Linguist and academic. Founded Appen in Sydney in 1996. She pioneered speech and text recognition technology.
Chris Vonwiller
Senior executive at Telstra at the time of founding. Joined Appen in 2000 and served as Non-Executive Chairman.
Executive Team
Ryan Kolln
Chief Executive Officer and Managing Director
Over 20 years of global experience in technology and telecommunications. Started career as an engineer focused on mobile network data engineering in Australia, Asia and North America. MBA from New York University. Joined The Boston Consulting Group (BCG) in 2011 as a strategy consultant. Joined Appen in 2018 as VP of Corporate Development, leading strategic acquisitions like Figure Eight and Quadrant. Served as Chief Operating Officer before becoming CEO in February 2024.
Justin Miles
Chief Financial Officer
Over 20 years of experience in listed companies within technology and services sectors. Joined Appen in 2016, served over 5 years as Vice President Finance. Promoted to Interim CFO in August 2023, officially appointed CFO in February 2024. Previously Group Financial Controller at Rubicor Group Ltd. Holds Bachelor of Business (Accounting).
Board of Directors
Founding Story
Appen was founded in Sydney in 1996 by linguist Dr. Julie Vonwiller and her husband Chris, a senior executive at Telstra. The company was established to pioneer speech and text recognition technology. The Vonwillers built the company from linguistic technology innovation into a global leader in AI data annotation. In 2009, Anacacia Capital acquired a 51% share of Appen as the Vonwillers sought to expand operations.
Business Model
Revenue Model
B2B revenue model based on providing AI data services including data annotation, collection, labeling services, AI platform subscriptions, and crowd-sourced workforce solutions. Revenue generated through API usage, project-based contracts, and enterprise platform subscriptions. Services priced on unit-based and hourly models.
Target Markets
- Technology companies
- Automotive industry
- Retail and eCommerce
- Financial services
- Government and public sector
- Healthcare
- Data Labeling
- LLM Fine-Tuning
- Model Distillation
- Red Teaming
- Retrieval-Augmented Generation (RAG)
- Search Relevance
- Eight of the top ten global technology companies
- Amazon
- Microsoft
- Salesforce