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AI data platform iMerit<\/a> believes the next step towards integrating AI tools at the enterprise level is not more data, but better data. And better data doesn\u2019t come from hordes of gig workers, but from experts across mathematics, medicine, healthcare, finance, autonomy, and other cognitive fields, the company says. <\/p>\n \u201cWhat\u2019s become exceedingly important is the ability to attract and retain the best cognitive experts, because we have to take these large models and make them very customized towards solving enterprise AI problems,\u201d Radha Basu, CEO and founder of iMerit, told TechCrunch.\u00a0<\/p>\n The California- and India-based startup has for the past nine years quietly built itself into a trusted data annotation partner for companies working in computer vision, medical imaging, autonomous mobility, and other AI applications that require high-accuracy, human-in-the-loop labeling.\u00a0<\/p>\n Now, iMerit is bringing its Scholars program out of beta, the company exclusively told TechCrunch. The goal of the program is to build a growing workforce of experts to fine-tune generative AI models for enterprise applications and, increasingly, foundational models.\u00a0<\/p>\n iMerit already calls some of the top AI firms customers, including three of the big seven generative AI companies, eight of the top autonomous vehicle companies, three large U.S. government agencies, and two of the top three cloud providers, according to the company.<\/p>\n The news comes as Scale AI, arguably the biggest name in AI data annotation, has lost its founder and CEO Alexandr Wang to Meta<\/a>, which also acquired a 49% in the company<\/a>. In the wake of Meta\u2019s investment, many of Scale\u2019s major clients pulled back, including Google, OpenAI, Microsoft, and xAI, out of concerns that Meta could gain access to their product roadmaps.\u00a0<\/p>\n iMerit doesn\u2019t claim to replace Scale AI\u2019s core offering of high-throughput, developer-focused \u2018blitz data.\u2019 Instead, it\u2019s betting that now is the right moment to double down on expert-led, high-quality data, the kind that requires deep human judgment and domain-specific oversight.<\/p>\n \u201cWe\u2019re the adults in the room,\u201d Rob Laing, iMerit\u2019s VP of global specialist workforce, told TechCrunch. \u201cA lot of money is being spent on AI right now. There are some very intelligent people building large platforms of human workforces. The output that they\u2019re getting from that mass approach and that very quick speed to market approach is not at the level of quality that enterprises need.\u201d<\/p>\n Basu brought up the example of healthcare scribes that have come to market off the back of foundational large language models.<\/p>\n \u201cIf you don\u2019t have the expertise of the cardiologist or the physician, what you\u2019re doing is basically creating something that\u2019s maybe 50% or 60% accurate,\u201d Basu said. \u201cYou want that to be 99%. You want to question the model. You want to break it. You want to fix it. That is what expert-led AI is making possible for enterprise.\u201d<\/p>\n iMerit\u2019s experts are tasked with finetuning, or \u201ctormenting,\u201d enterprise and foundational AI models using the startup\u2019s proprietary platform Ango Hub. Ango allows iMerit\u2019s \u201cScholars\u201d to interact with the customer\u2019s model to generate and evaluate problems for the model to solve.\u00a0<\/p>\n For iMerritt, attracting and retaining cognitive experts is key to success because the experts aren\u2019t just doing a few tasks and disappearing; they\u2019re working on projects for multiple years. iMerit boasts a 91% retention rate, with 50% of its experts being women.\u00a0<\/p>\n