Many AI startup ideas are still little more than superficial “wrappers” that build on existing models. But as AI model makers add more capabilities, investors are wary of startups that could so easily become redundant.
Case in point: when reviewing more than 4,000 applications for the joint AI startup accelerator in India run by Google and venture firm Accel, “wrapper” ideas dominated. But none of them were among the five startups for the latest cohort, Accel partner Prayank Swaroop (pictured above) told TechCrunch.
Announced in November, the AI-focused Atoms program from Google and Accel aims to support early-stage startups building India-connected AI products. Startups selected for the latest cohort will receive up to $2 million in funding from Accel and Google’s AI Futures Fund, along with up to $350,000 in cloud computing and AI credits from Google, the companies said.
About 70% of rejected apps were “wrappers” — startups that layered AI features like chatbots on top of existing software, but “were not redesigning new workflows using AI,” Swaroop said.
Many of the remaining rejected applications, Swaroop said, fell into crowded categories like marketing automation and artificial intelligence recruiting tools, areas where investors saw little innovation. Startups in these sectors often struggle to differentiate themselves, he said.
This, perhaps, is not surprising. This year’s program received nearly four times as many applications as Accel’s previous Atoms cohorts — with many first-time founders.
India’s growing AI ecosystem remains largely focused on enterprise applications, and Swaroop said the applications reflect that. About 62% of the submissions focused on productivity tools and another 13% on software development and coding, meaning about three-quarters of the applications were business software ideas rather than consumer products. (Swaroop hoped to see more ideas for health care and education.)
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Jonathan Silber, co-founder and director of Google’s AI Futures Fund, said the five startups chosen closely align with areas where Google expects AI to see deeper real-world adoption.
The program doesn’t require startups to use Google’s 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 about how Google’s models perform in real-world applications.
Information from these startups can then be fed back to Google’s DeepMind teams to help improve future models, creating what Silber described as a “flywheel” between startup experimentation and AI development. “If a company is using an alternative model, that means Google has work to do to create the best model in the market,” he told TechCrunch.
The startups selected this year are:
- K-Densewhich creates an AI “co-scientist” to accelerate research in areas such as life sciences and chemistry.
- Dodge.aiwhich develops autonomous agents for enterprise ERP systems.
- Persistence Labswhich focuses on voice AI for call center operations;
- Zingrollwhich is building a platform for AI-generated movies and shows.
- Flat levelwhich applies artificial intelligence to industrial automation in automotive and aerospace manufacturing.
