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Playment

Winter 2017Acquired

Mechanical Turk for enterprises.

Save
Playment logo

Playment

Winter 2017Acquired

Mechanical Turk for enterprises.

Save
Company details

"Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate and brilliant; together they are powerful beyond imagination."​

Playment is a fully managed data labeling platform generating training data for computer vision models at scale. We empower companies in the Autonomous Vehicle, Drones, Mapping, and similar spaces with high precision annotation services - No matter how complex. We’re helping companies and research institutions like Drive AI, Starsky Robotics, CYNGN, and UIUC focus on their core areas of development.

Our platform is powered by a trained workforce of 300,000+ users and managed by our human intelligence experts who build your tasks and deliver results with assured quality.

Support Annotation types: Bounding Boxes, Cuboids, Polygons, and Polylines, Point annotations, Segmentation(coming soon) for both image and video data types. Interested to hear more? please check out https://playment.io

Use Cases we worked on: Autonomous vehicles, drones, satellite imagery, precision agriculture, Retail / eCommerce, sports analytics

Location
Bengaluru, KA, India
Founded
2015
Category
Crowdsourcing
YC Directory Pageplayment.io
Founder
  • AL
    Akshay Lal
    Co-Founder & Head of Product
    LinkedIn

"Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate and brilliant; together they are powerful beyond imagination."​

Playment is a fully managed data labeling platform generating training data for computer vision models at scale. We empower companies in the Autonomous Vehicle, Drones, Mapping, and similar spaces with high precision annotation services - No matter how complex. We’re helping companies and research institutions like Drive AI, Starsky Robotics, CYNGN, and UIUC focus on their core areas of development.

Our platform is powered by a trained workforce of 300,000+ users and managed by our human intelligence experts who build your tasks and deliver results with assured quality.

Support Annotation types: Bounding Boxes, Cuboids, Polygons, and Polylines, Point annotations, Segmentation(coming soon) for both image and video data types. Interested to hear more? please check out https://playment.io

Use Cases we worked on: Autonomous vehicles, drones, satellite imagery, precision agriculture, Retail / eCommerce, sports analytics

Location
Bengaluru, KA, India
Founded
2015
Category
Crowdsourcing
YC Directory Pageplayment.io
Founder
  • AL
    Akshay Lal
    Co-Founder & Head of Product
    LinkedIn

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On this page
  • Overview
  • Founding Story
  • Timeline
  • What They Built
  • Market Position
  • Target Customers
  • Market Size
  • Competition
  • Business Model
  • Traction
  • Post-Mortem
  • Workflow depth outlasted the generic crowd
  • Confidential work forced a second operating model
  • Enterprise distribution favored consolidation
  • The counter-narrative: acquisition validated the pivot
  • Key Lessons
  • Sources

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Exec Briefing

Actionable insights

If you only have a few minutes to spare, here’s what investors, operators, and founders should know about Playment (W17).

  1. Task design became the moat. A large contributor pool supplied capacity, but repeatable instructions, reviewer calibration, and specialist tools made complex computer-vision work defensible.
  2. Confidentiality changed the cost base. Moving sensitive projects into secure BPO partners unlocked enterprise demand while adding facilities, training, and quality labor to delivery economics.
  3. A narrow vertical sharpened the product. Autonomous-driving demand pulled a general catalog-work marketplace toward cuboids, tracking, segmentation, and LiDAR workflows that justified annual contracts.
  4. Distribution completed the asset. The buyer paired Playment's computer-vision depth with global procurement, customer relationships, and more than one million annotators.
  5. Strategic fit does not reveal returns. Product survival and team integration show operating value; undisclosed consideration and ownership terms leave the founder and investor outcome unknown.

Overview

Playment began in Bengaluru in 2015 as a mobile marketplace for small human data tasks. The founders first applied it to e-commerce catalog work, then narrowed the company around managed training data for computer vision. By the time of its exit, Playment combined annotation software, project design, quality control, and a secure workforce for image, video, and LiDAR projects.

This was a successful capability sale. Playment learned that enterprise labeling required much more than a large crowd. Customers bought workflow design, security, specialist labor, and accountable quality. TELUS International already had global sales and more than one million annotators, so buying Playment accelerated its computer-vision product depth.[1] The acquisition completed on July 2, 2021; its price was not disclosed.[2]

Playment co-founders Akshay Lal, Ajinkya Malasane, and Siddharth Mall at Y Combinator
Akshay Lal, Ajinkya Malasane, and Siddharth Mall at Y Combinator in 2017, as Playment was turning a general crowd-work app into computer-vision infrastructure.

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Founding Story

Siddharth Mall, Ajinkya Malasane, and Akshay Lal met through India's IIT network and later worked at Flipkart. Akshay worked on catalog products; Siddharth and Ajinkya helped build Flipkart's crowdsourced hyperlocal delivery operation. At Flipkart, they watched a captive business-process-outsourcing team of more than 500 people handle catalog operations while product volume changed unpredictably. Siddharth told YourStory: "We struggled to scale the team as millions of products got added to the catalogue."[3]

They started Playment in 2015 with Himanshu Sahu, an IIT Kharagpur classmate who had worked at Babajob. The first idea was a mobile app that broke catalog cleanup, content moderation, and other data operations into short tasks. Contributors, called players, chose work on their phones and earned rewards. Enterprises sent data through APIs; Playment split a project into microtasks, routed them to qualified workers, and aggregated the results.

The consumer crowd supplied elasticity, but enterprise buyers needed accuracy. Ajinkya told VentureBeat: "Legacy crowdsourcing platforms such as [Amazon's Mechanical Turk] don't assure quality."[4] Playment therefore sold a managed outcome instead of access to workers. Its software encoded task design, worker qualification, redundancy, and checking.

Customer demand then pulled the company toward computer vision. In 2017, Playment added bounding boxes, 3D cuboids, points, lines, and polygon segmentation. Autonomous-driving teams needed people to identify pedestrians, lanes, vehicles, and unusual road objects across large image and video sets. By November 2017, about 70% of Playment's roughly 30 customers were in autonomous driving.[4] The company had found a narrower, higher-value use for the operating system it first built for retail catalogs.

Timeline

  • August 2015: Playment was founded in Bengaluru by former Flipkart operators and IIT alumni.[3]
  • July 2016: SAIF Partners invested a reported $700,000 seed round.[5]
  • Winter 2017: Playment joined Y Combinator.[6]
  • November 2017: The company announced $1.6 million from YC, Sparkland Capital, SAIF Partners, Ryan Petersen, Max Altman, and others.[4]
  • 2017: Team size reached 40; Playment reported 300,000 qualified players and more than one million annotations per week.[7]
  • 2019: The company shifted most confidential work to secure BPO partners while retaining crowdsourcing for suitable projects.[8]
  • 2020: Inc42 reported that Playment became profitable; Forbes reported more than 100 customers, 1,000 full-time workers, and 300,000 freelancers.[8][9]
  • July 2, 2021: TELUS International completed its acquisition of Playment for an undisclosed amount.[2]
  • July 6, 2021: TELUS and Playment announced the transaction publicly.[1]

What They Built

Playment sold a full labeling operation. A customer uploaded images, video, or sensor data and described the model behavior it wanted to teach. Playment's team translated that goal into label definitions and instructions, configured a project, trained workers, and returned checked annotations through files or APIs.

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