Mars Finance reports that Sydney Huang, a graduate of Babson College, announced the launch of Human API today. This is a brand-new platform designed to enable AI systems to directly collaborate with humans, acquiring real-world data and labor. Huang also serves as the CEO of Eclipse Labs, the company behind Human API. “AI agents are no longer limited by their intelligence levels,” Sydney Huang stated, “what they are restricted by is access to the physical world. The existence of Human API is precisely to bridge this gap.” Human API aims to address what the company calls the “last mile problem” of autonomous AI agents. Although modern agents can reason, plan, and execute tasks within digital environments, many activities with economic value still require human participation, such as delivery completion, data collection, and interaction with institutions that have not yet integrated APIs. Human API provides a standardized interface for agents to request, coordinate, and pay humans to complete these tasks. In its initial launch phase, the platform will focus on voice data, which is one of the most restricted input modalities in current AI systems. Audio is a highly information-dense modality, containing language, accents, emotions, timing, and background environment information. However, due to authorization restrictions, compression artifacts, and lack of metadata, high-quality, annotatable audio data is difficult to collect at scale. As a result, many speech and multimodal models perform poorly on non-English languages, regional accents, bilingual speech, overlapping conversations, and subtle emotional expressions. Human API enables contributors worldwide to provide high-quality multilingual audio using standard consumer-grade devices, significantly lowering participation barriers. The company states that this approach allows AI systems to access data that cannot be reliably scraped or generated through synthesis. Although still in stealth mode, Human API has completed its first paid data deliveries to enterprise clients, validating market demand—on one side, buyers seeking higher coverage datasets, and on the other, contributors willing to provide such data. David Feiock, General Partner at Anagram and investor in Human API, said, “AI agents are strong at reasoning but still face challenges in the last mile because that requires coordination, data collection, and human judgment. The appeal of Human API is that it treats humans as infrastructure. It’s not a managed service or a generalized crowdsourcing platform, but a human-in-the-loop approach focused on agents and rights protection, integrating humans into the system with real-time payments.” Human API plans to expand beyond voice to include more forms of human-provided data and real-world task execution in the future. Currently, the platform is accepting contributor registrations at thehumanapi.com.
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Sydney Huang launches the native platform Human API for intelligent agents, aiming to enable AI systems to directly hire humans
Mars Finance reports that Sydney Huang, a graduate of Babson College, announced the launch of Human API today. This is a brand-new platform designed to enable AI systems to directly collaborate with humans, acquiring real-world data and labor. Huang also serves as the CEO of Eclipse Labs, the company behind Human API. “AI agents are no longer limited by their intelligence levels,” Sydney Huang stated, “what they are restricted by is access to the physical world. The existence of Human API is precisely to bridge this gap.” Human API aims to address what the company calls the “last mile problem” of autonomous AI agents. Although modern agents can reason, plan, and execute tasks within digital environments, many activities with economic value still require human participation, such as delivery completion, data collection, and interaction with institutions that have not yet integrated APIs. Human API provides a standardized interface for agents to request, coordinate, and pay humans to complete these tasks. In its initial launch phase, the platform will focus on voice data, which is one of the most restricted input modalities in current AI systems. Audio is a highly information-dense modality, containing language, accents, emotions, timing, and background environment information. However, due to authorization restrictions, compression artifacts, and lack of metadata, high-quality, annotatable audio data is difficult to collect at scale. As a result, many speech and multimodal models perform poorly on non-English languages, regional accents, bilingual speech, overlapping conversations, and subtle emotional expressions. Human API enables contributors worldwide to provide high-quality multilingual audio using standard consumer-grade devices, significantly lowering participation barriers. The company states that this approach allows AI systems to access data that cannot be reliably scraped or generated through synthesis. Although still in stealth mode, Human API has completed its first paid data deliveries to enterprise clients, validating market demand—on one side, buyers seeking higher coverage datasets, and on the other, contributors willing to provide such data. David Feiock, General Partner at Anagram and investor in Human API, said, “AI agents are strong at reasoning but still face challenges in the last mile because that requires coordination, data collection, and human judgment. The appeal of Human API is that it treats humans as infrastructure. It’s not a managed service or a generalized crowdsourcing platform, but a human-in-the-loop approach focused on agents and rights protection, integrating humans into the system with real-time payments.” Human API plans to expand beyond voice to include more forms of human-provided data and real-world task execution in the future. Currently, the platform is accepting contributor registrations at thehumanapi.com.