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EXL to Buy iMerit for Up to $310M to Boost AI Capabilities

Summarized from GlobalNewswire

ExlService Holdings is acquiring AI training specialist iMerit for up to $310M, targeting foundation model expertise and high-growth AI tech markets.

ExlService Holdings (NASDAQ: EXLS) just made its biggest AI bet yet. The New York-based data and AI company announced a definitive agreement to acquire iMerit, a specialist in AI model training, evaluation, and reinforcement learning — and it's paying up to $310 million in upfront and future consideration to get it done.

iMerit is not a random pickup. The company is known specifically for helping clients train large language models and multimodal AI systems, improving their accuracy and precision. That's exactly the infrastructure layer that enterprise AI needs right now, and EXL is planting its flag squarely in the middle of it.

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The deal is expected to close in Q3 2026, pending standard closing conditions. Once it clears, EXL gains direct access to the foundation model ecosystem — including partnerships with leading AI builders — and a stronger foothold in high-growth AI tech sectors that are drawing serious capital attention.

For EXLS shareholders and traders watching the AI services space, this signals a clear strategic pivot from analytics-and-outsourcing toward owning the AI supply chain. If enterprises are going to spend heavily on AI outcomes, EXL wants a cut of the model-building side, not just the consulting wrapper around it. That's a differentiated angle in a crowded field.

Continue reading at GlobalNewswire.

Frequently Asked Questions

Q.How much is EXL paying to acquire iMerit?

EXL has agreed to pay up to $310 million in upfront and future consideration to acquire iMerit.

Q.When is the EXL and iMerit deal expected to close?

The acquisition is expected to close in the third quarter of 2026, subject to customary closing conditions.

Q.What does iMerit specialize in?

iMerit specializes in AI model training, evaluation, and reinforcement learning, helping clients train large language and multimodal models to improve accuracy and effectiveness.

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