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Many artificial intelligence startup ideas are still little more than superficial \u201cwrappers\u201d built on top of existing models. But as the AI model makers add more features, investors are wary of startups that could become so easily unnecessary.<\/p>\n
Case in point: when reviewing more 4,000 applications for the joint AI accelerator for India startups run by Google and venture firm Accel, \u201cwrapper\u201d ideas dominated. But none of them were among the five startups for the latest cohort, Accel partner Prayank Swaroop told TechCrunch (pictured above).<\/p>\n
Announced<\/a> in November, the AI-focused Atoms program by Google and Accel aims to back early-stage startups building AI products linked to India. Startups selected for the latest cohort will receive up to $2 million in funding from Accel and Google\u2019s AI Futures Fund<\/a>, along with up to $350,000 in cloud and AI compute credits from Google, the firms said.<\/p>\n Roughly 70% of the rejected applications were \u201cwrappers\u201d \u2014 startups that layered AI features such as chatbots on top of existing software but \u201cwere not reimagining new workflows using AI,\u201d Swaroop said.<\/p>\n Many of the remaining applications that were denied, Swaroop said, fell into crowded categories such as marketing automation and AI recruitment tools, areas where investors saw little novelty. Startups in those sectors often struggle to differentiate themselves, he said.<\/p>\n This isn\u2019t, perhaps, surprising. This year\u2019s program received nearly four times the applications than previous Accel\u2019s Atoms cohorts \u2014 with many first-time founders.<\/p>\n India\u2019s growing AI ecosystem remains largely focused on enterprise applications and Swaroop said the applications reflected that. About 62% of the submissions focused on productivity tools and another 13% on software development and coding, meaning around three-quarters of the applications were enterprise software ideas rather than consumer products. (Swaroop had hoped to see more ideas for healthcare and education.)<\/p>\n Techcrunch event<\/p>\n \n\t\t\t\t\t\t\t\t\tSan Francisco, CA<\/span> Jonathan Silber, co-founder and director of Google\u2019s AI Futures Fund, said the five startups selected aligned closely with areas where Google expects AI to see deeper real-world adoption.<\/p>\n The program does not require startups to use Google\u2019s models exclusively, Silber said, noting that many companies combine multiple models depending on the workflow. The goal, he said, is to gather feedback from startups on how Google\u2019s models perform in real-world applications.<\/p>\n Insights from those startups can then be fed back to Google DeepMind teams to help improve future models, creating what Silber described as a \u201cflywheel\u201d between startup experimentation and AI development. \u201cIf a company is using an alternative model, that means Google has work to do to build the best model in the market,\u201d he told TechCrunch.<\/p>\n This year\u2019s startups selected are:<\/p>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\tOctober 13-15, 2026<\/span>\n\t\t\t\t\t\t\t<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n\n