For instance, sellers often bulk upload apparel catalogues on ecommerce platforms. A person on the ecommerce platform has to inspect each and every item submitted before it is published to ensure that the products are labelled in a way that buyers can find easily. Playment simplified it allowing products to be identified by machine learning. The startup, 70% of whose clients are automakers, helps the self learning software of its clients identify objects.
- Managing 1000s of annotators every day requires an analytics-led approach in the remote set up.
- While we started out with a deep focus on autonomous driving use cases, this year we expanded with other industries like agriculture, real estate, mining, and defense among others.
- We have built a new website with first-of-its-kind information to give our community a peek into what really goes behind building data labeling infrastructures that produce high-quality training and ground truth data.
- The global data annotation tools market size was estimated at $321.45 Mn in 2020, according to a report by Expert Market Research.
- The different tools available are 2D Bounding boxes, Semantic Segmentation, Cuboids, Polygons, Polylines, Landmarks.
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It offers software solutions to build high-quality visual data labels- a process known as data annotation. The startup works with more than 200 machine learning teams across global companies. Playment’s GT Studio offers ML-assisted 2D and 3D labeling tools.
Playment Product and Pivots
After signing up, the users are taken to the management dashboard which is light in color. To maintain visual uniformity in the journey, we chose to go ahead with the light colored illustration. Unlock special offers and join 10,000+ founders, investors & operators staying ahead in India’s startup economy.
Data Annotation And Computer Vision Opportunities
This year, we spent more than a few late nights developing a product that makes data labeling more accessible to ML teams. As more and more companies were going remote, we saw the need for a high-performing web-based labeling platform. A low-code platform that anyone anywhere can use to label datasets and manage 100s of labeling pipelines seamlessly. We also gave early access to a few of our customers and teams interested in exploring a data labeling platform that’s perfect for remote setups. Our beta customers have more than 350+ full time labelers working on GT Studio. Playment was launched in November 2015 by former Flipkart employees- IIT-Kharagpur alumni Siddharth Mall and Akshay Lal, along with IIT-Guwahati alumnus Ajinkya Malasane.
Project ID
- We tried several background colors and illustration dimensions.
- The points can be exchanged in the form of vouchers on online e-commerce sites.
- They empower high precision annotation services with complex customizations.
- Currently, Playment services a host of international clients including Samsung, German automotive tools giant ZF, US-based self driving solution company Nuro and Daimler AG among others.
- From fun sing-off sessions to virtual heists and group competitions, our time working from home was not-so-dull.
It was in the process of looking out for partners and investors in the business that Playment founders engaged with TELUS leading to the eventual gt studio playment acquisition. All 85 of the startup’s employees, including founders, will join TELUS post acquisition. This dashboard allows us to set up and monitor customized workflows and build an end to end project management with playment workforce. ML engineers can use Python code to integrate their pipelines.
Project progress and quality analytics with active feedback are also provided keyboard shortcuts, visualization tools and confusion metrics. Since the future of work is remote, there is an increasing demand for web-based annotation tools compared to offline tools. Managing 1000s of annotators every day requires an analytics-led approach in the remote set up. The focused ML efforts of 2020 will fuel the emergence of self-driving cars as early as 2021.
In the initial years, Playment used to work with crowd-sourced data annotators who would do the labelling work. This demand for data annotation solutions also helped the company become profitable in 2020. The global data annotation tools market size was estimated at $321.45 Mn in 2020, according to a report by Expert Market Research.
In 2015, the team started with providing cataloging and content moderation services to large marketplaces such as Flipkart, Lazada, Paytm, Ola and others. “At Flipkart, we used to address a lot of repetitive cataloguing requirements. Especially because a lot of sellers did not know how to categorise their products properly. This led us to build the Playment solution,” said Malasane speaking to Inc42. The platform is powered by a workforce of 300,000+ users which is managed by the human intelligence experts who build the tasks and deliver results with assured quality. Playment has been proactively working on creating infrastructures that offer maximum flexibility and scalability.
Thriving in the new normal came with its own challenges, yet, we were well-prepared to go remote because of our web-based labeling platform and pre-established collaboration and communication protocols. We executed more than 776,475 hours of labeling and shipped ~64M high-quality annotations remotely for our customers worldwide. As a 2D/3D annotation tool and a platform to manage labelling teams of any size with team management software, all in one place, we wanted to communicate our distinguishing features through it. Globally, most companies outsource data labelling jobs to dedicated data annotators. Data labelling takes up the bulk of data scientists’ time, which could otherwise have been devoted to building algorithms. As in case of technology outsourcing opportunities, India has emerged as a leading data labelling destination globally.
The data annotation tool market is projected to record a CAGR of 27% between 2021 and 2026. The market growth is largely attributed to the increased adoption of software for image data annotation in the automotive, retail, and healthcare sectors. While artificial intelligence drives a lot of solutions globally, little is understood about how it works. Playment particularly deals with AI and machine learning software of the visual kind. Suppose an automobile manufacturer wants to build self-driven cars.
Lidar sensors available in the new iPhones have also bolstered the adoption rates. Playment will continue to build cutting-edge tools for lidar sensors in the upcoming year. We have built a new website with first-of-its-kind information to give our community a peek into what really goes behind building data labeling infrastructures that produce high-quality training and ground truth data. In India it competes with data annotation companies like iMerit and Infolks.
Data Annotation is not only limited to image and video but now with recent advances in computer vision, it is extended to sensors even. After creating the job, please store the job_id received in the response. None of this would have been possible without the people working behind the scenes. From taking pay cuts during the pandemic to giving more than 100% effort for all our projects, we could not have asked for a better team. From fun sing-off sessions to virtual heists and group competitions, our time working from home was not-so-dull. All credits go to our excellent HR Manager, Sahiba Chandok, who has created an inclusive and fun work culture at Playment.
We divert their time to improve the quality of our deliverables with various QC tools and processes. We took forward two designs and discussed the pros and cons of each. CabinetM helps modern marketing and sales teams manage the technology they have and find the tools they need.