EXL acquires physical AI model developer iMerit
Radha Basu, EVP and head of iMerit (left), and Rohit Kapoor, CEO of EXL (right).

Radha Basu, EVP and head of iMerit (left), and Rohit Kapoor, CEO of EXL (right). Credit: Mark Liflander, EXL
The actions of physical AI, including robots, are only as good as the human expertise and data used to build the AI models that train them. ExlService Holdings Inc. this month completed its acquisition of iMerit Technology, a leader in AI model training, evaluation, and reinforcement learning.
Founded in 1999, EXL offers services and solutions to industries including insurance, healthcare , banking and capital markets, retail, communications and media, and energy and infrastructure. The New York-based company has about 68,000 employees worldwide.
Founded in 2012, iMerit provides data annotation for robotics, autonomous mobility, healthcare AI , and other high-tech industries. The San Jose, Calif.-based company said its subject-matter experts and proprietary Ango Hub platform enable customers “to collaborate on complex multimodal data to generate highly curated and validated training artifacts for high-stakes models.”
For instance, iMerit has partnered with Carbon Robotics to help digest millions of plant images needed to create an agricultural model for robotic weeding.
Radha Ramaswami Basu , founder and CEO of iMerit, has joined EXL as executive vice president and head of iMerit. She and Rohit Kapoor , chairman and CEO of EXL, replied to the following questions from The Robot Report about the acquisition.
What challenges are AI model builders underestimating today, and why?
Basu: Models are becoming highly capable day by day. With this comes increasing potential for hallucination or exceeding the scope. The labs, like customers, are starting to realize that the final mile and the concept of trust need work in order to thrive in a critical enterprise process.
A model can perform well on a benchmark and still struggle with edge cases, unfamiliar conditions, or the specialized context of a healthcare or financial workflow. The bottleneck is access to expert, domain-specific data and trusted deployment in a business workflow.
This is solved by experts who can challenge the model, expose failure modes, and evaluate whether its reasoning and behavior are reliable in a given business environment.
How does EXL’s acquisition of iMerit change how models are trained and evaluated?
Kapoor: The acquisition connects parts of the AI lifecycle that have often been managed separately, establishing an end-to-end AI platform for enterprises.
Source: The Robot Report