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Anthropic begins local inference for AI models to process data in India

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Anthropic begins local inference for AI models to process data in India

Anthropic begins local inference for AI models to process data in India

Anthropic will process Claude requests on servers in India through Amazon Bedrock, giving banks, government bodies and other regulated organisations greater data residency and compliance controls. Reliance, CRED and other customers have already tested the service in private preview.

Artificial intelligence major Anthropic on Monday said it has started providing AI inference within India through Amazon Bedrock, enabling its AI models, including Claude Opus 5, Sonnet 5, and Haiku 4.5, to process data within the country’s jurisdiction. This means that when a query is generated in Claude AI, the response will be delivered after processing the query on servers located in India. The move follows requests from Indian entities to comply with local data processing norms as per the Digital Personal Data Protection Act.

The Claude AI model deployments through Amazon Bedrock in India will provide audit trails and access controls that risk and compliance teams require before deploying AI in production environments, the company said in a statement. ”In August, we committed to bringing Claude inference to India, and we are delivering on that promise. Our customers, especially in regulated sectors and government, want to use Claude on their most critical work, with requests processed in the country. From today, they can,” Anthropic Managing Director for India Irina Ghose said. She said that it is a long-term commitment from Anthropic and the company will keep growing its team in India and investing in local partnerships. Also read: How banks, insurers and brands are exploring AI-led consumer discovery ”Requests sent to Claude through the India endpoint are now processed within India, giving regulated Indian institutions the data residency assurances they need to deploy Claude at scale across their most sensitive workloads,” Anthropic said.


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