Sarvam AI and Ridlan AI Foundation awarded for empowering people with disabilities

Sarvam AI and Ridlan AI Foundation awarded for empowering people with disabilities

People with disabilities face barriers in communication and access. The Mint All About AI Tech4Good Awards recognised Sarvam AI for its localised AI solutions enhancing accessibility and Ridlan AI...

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Rezo.ai and Nivinsure honoured for financial inclusion at the Mint All About AI Tech4Good Awards

Rezo.ai and Nivinsure honoured for financial inclusion at the Mint All About AI Tech4Good Awards

Despite a rise in the Financial Inclusion Index to 64.2, many in India remain excluded from credit and insurance. AI tools like Rezo.ai and Nivinsure are addressing these gaps, streamlining processes...

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EcogenX Innovations and ST Engineering win for sustainable solutions at the Mint All About AI Tech4Good Awards

EcogenX Innovations and ST Engineering win for sustainable solutions at the Mint All About AI Tech4Good Awards

India's $5 trillion GDP goal relies on sustainability through AI. EcogenX Innovations and ST Engineering received awards for advancements in waste management and urban infrastructure, respectively,...

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India proposes sweeping AI–copyright overhaul with ‘one nation, one licence, one payment’ model

India proposes sweeping AI–copyright overhaul with ‘one nation, one licence, one payment’ model

The proposal is the government’s first formal policy outline in an area that has sparked intense global debate over the future of intellectual property. It comes in the wake of soaring AI adoption,...

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Govt rolls out 12 new standards across AI, payments security, audit data and industrial systems

Govt rolls out 12 new standards across AI, payments security, audit data and industrial systems

The new AI data-quality standards are particularly significant, aiming to improve accountability and reduce bias in regulated sectors.

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Legal tech is flush with capital—but drowning in data cleanup

Legal tech is flush with capital—but drowning in data cleanup

The promise of automation in the legal sector faces a major structural hurdle: the tedious process of cleaning and annotating messy, unstructured legal data to make it machine-readable.

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