Data with a human touch
High-quality data for machine learning, enhanced by human interaction
The Appen difference
Trusted by 8 out of the top 10 global technology companies
Our skilled project managers use multiple quality control methods and mechanisms to meet and exceed quality standards for training data. Quality assurance is built into both the platform and processes at Appen.
With a crowd of over 1 million skilled contractors operating in 130+ countries and 180+ languages and dialects, Appen can collect and label high volumes of image, text, speech, audio, and video data used to build and improve artificial intelligence systems.
Our platform and solutions are purpose-built to handle large-scale data collection and annotation projects, on demand. With deep expertise planning and recruiting to meet a variety of uses cases for our clients, we can quickly ramp up new projects in new markets.
Appen provides multiple secure service offerings, including secure remote contractors, on-site contractors, on-premise solutions, and ISO 27001 / ISO 9001 accredited secure facilities.
Appen at a glance
- Experience working in
- Expertise in
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- Over 600 employees located in nine offices around the globe
- Access to a curated crowd
of over 1 million flexible contractors worldwide
- More than 3 billion
judgments made and 500,000 hours of audio processed
- 20+ years working
with leading global
- Top 100 Language Service ProvidersCSA Research
- #1 Company to Watch 2019FlexJobs
- People’s Choice AwardSpeech Technology Magazine
- The Donor AwardTranslators Without Borders
- Technology Fast 500 APAC WinnerDeloitte
- Appen’s text-to-speech conversion has been pivotal in helping us provide more information in more ways and helping patients understand what they’re taking.”Anna Paonne, Key Account and Business Development Manager
- The Appen team was a joy to work with. They demonstrated clear expertise in developing our training data and delivered it ahead of schedule and under budget.”Dr. Catriona Wallace, FlamingoAI CEO
- The relationship we have with Appen makes all the difference to our success. The Appen team is a part of our team and is just as committed to quality as we are. It’s the type of dynamic you don’t find every day.”A leading search engine provider
- Appen’s ability to prioritize and stay within the designated budget allows us to successfully deliver quality results within short deadlines. They’ve proven to be an invaluable resource.”Major international software provider
- We had strict quality standards that needed to be implemented. This required close collaboration. The Appen team partnered with us to develop task guidelines and quality management plans. They quickly ramped the number of participants needed to meet daily and weekly data demands. Their effectiveness ensured the success of this project.”Global social network provider
- We needed to offer consumers more personalization on our site. Partnering with Appen allowed us to collect high-quality training data for our machine learning model, which refined our algorithm much more quickly and consistently than we’ve been able to in the past.”Major international software provider
The Appen Blog
Get the latest news and insights by visiting the Appen Blog
Appen Announces Crowd Code of Ethics
The initiative reflects the importance of the Crowd’s well-being in creating the data for AI systems and applications that people worldwide increasingly use and depend on every day.
AI in Police Work
At Appen, we provide high-quality training data for machine learning and artificial intelligence. Follow us to stay up to date on industry trends. In this edition of our roundup, news on AI in police work. Check back for regular news roundups and subscribe to our YouTube channel for video updates. Can AI Help Police Officers Solve Crimes? Law enforcement is …
A Driverless Future Will Impact All of Us
In all cases, a driverless future is coming … the question that remains is when.
Trends in the Zettabyte Era
Without a well-defined strategy for collecting and structuring the data you need to train, test, and tune your AI systems, you run the risk of delayed projects, not being able to scale appropriately, and ultimately, competitors outpacing you.
What Does Interoperability Mean for the Future of Machine Learning?
For years, interoperability — the ability for two systems to communicate effectively — has been an important aspect of our increasingly digitalized world. For banking, healthcare, and other everyday industries, we’ve come to expect that the platforms we use to exchange information can communicate seamlessly whenever we need them to. Because we all have hundreds of thousands of data points …
The Future of Artificial Intelligence in Healthcare
Expect to see dramatic changes in both patient health outcomes and in the operational efficiency of hospitals.
The Latest Innovations in Artificial Intelligence
What are some of the most recent developments in AI? With so many emerging applications for artificial intelligence making a splash across a wide range of industries, it can be difficult to keep up. This post will touch on some cool advances made in 2019 and look at what’s on the horizon. AI takes a deep dive Robotics is a …
AI Trends Disrupting Business
Organizations should have a reliable source of clean data to extract from and work with.
Common Sense AI: Making Deep Learning Technologies More Human
Whether through devices we use to enable convenience at home or in the way products we use all the time are manufactured, AI’s impact is everywhere, driving innovation in just about every aspect of our lives. But there are missing pieces to this puzzle that still cause frustration for end-users and present significant challenges for researchers trying to improve how AI technology performs.
O’Reilly San Jose: Creating Autonomy for Social Robots
This year’s O’Reilly AI conference in San Jose, CA delivered the usual mix of exciting presentations and dynamic discussions, as well as a healthy dose of industry networking. Appen is proud to have been given the opportunity to share some recent research at the conference that promises to improve the way robots interact with people. In their presentation Creating Autonomy …
Creating Chatbots and Virtual Assistants
Chatbots and their more sophisticated counterparts, virtual assistants, have emerged as a key tool to streamline customer service operations for organizations in a wide range of industries, and to help reduce costs.
Appen Fall 2019 Conference Rundown
Appen’s team of machine learning experts is excited to connect with you this fall. We’ll be exhibiting at industry conferences all over the world in the next few months and would love the opportunity to demonstrate how our high-quality training data can take your organization’s machine learning programs to the next level. Click here to schedule a meeting with the …
Appen Platform Unveils Feature Enhancements
Humans and Technology Working Together Enable Better AI Results SYDNEY — Aug. 20, 2019 — Appen Limited, the leading provider of datasets used by companies and governments to train AI systems quickly and at scale, today introduced feature updates for its AI training data solution designed to accelerate customers’ artificial intelligence initiatives. The Appen platform – already the most comprehensive …
How to Develop a Training Data Strategy
It’s well-known that the quantity and quality of training data for any given artificial intelligence (AI) project are two of the most crucial factors for that project’s success. Insufficient or poor training data can result in an unreliable system that reaches the wrong conclusions, makes poor decisions, can’t handle real-world variation, and introduces or perpetuates bias, among other problems. It’s …
Appen Strengthens Leadership Team with Key Executive Hires to Support Continued Growth
Sydney, NSW Australia – August 13, 2019 – Appen, a leader in the development of human-annotated training data used to build and continuously improve the world’s most innovative artificial intelligence systems, announces the hiring of two executives to its leadership team. Jon Kondo, Senior Vice President of Sales and Marketing; and Roc Tian, Senior Vice President of China, will support Appen’s …
CVPR 2019: Progress and Challenges in the Field of Computer Vision
The annual Computer Vision & Pattern Recognition conference is packed with insightful presentations and top industry experts. With nearly 10,000 attendees and 1,200 papers, CVPR 2019 in Long Beach, CA was no exception. In this post, we’ll take a brief look at some notable presentations delivered at the conference for solving numerous computer vision and pattern recognition challenges. Data augmentation …
Cost-Effective Crowdsourcing Strategies for Dialogue Systems
In a recent paper entitled Optimizing the Design and Cost for Crowdsourced Conversational Utterances, Appen data scientist Phoebe Liu and her team worked to identify cost-effective crowdsourcing strategies for training dialogue systems such as chatbots. Because more industries are adopting chatbot technology for customer service and other key functions, a need has emerged for training these systems as quickly and …
How to Solve Common Data Challenges in Conversational Design
When planning the development of a chatbot or virtual assistant, it’s important to begin the conversational design process with a clear data strategy in place. Conversational design requires more than just an understanding of the fundamentals of voice user interface design — you also need to understand how to solve some of the key challenges in data preparation. Working with the …
Appen on the Road: Events & Trade Shows this Summer
Appen is gearing up for some of the world’s leading industry events this summer. Our team will be exhibiting at conferences and trade shows around the globe, showing organizations how our services and solutions help develop high-quality training data for machine learning. Planning to attend one of these events? Contact us to set up a meeting with one of our …
5 Reasons to Outsource Your Data Annotation Projects
For many organizations, the temptation to annotate data for machine learning (ML) projects in-house is hard to deny. These companies typically feel that using internal resources will help them save time and money by tapping employees who are already on their payroll. Additionally, if their project is highly confidential or of a sensitive nature, they might feel that using internal …