Wirestock announced the closing of a $23 million Series A led by Nava Ventures with participation from SBVP, Formula VC, I2BF Global Ventures, as the company accelerates on its mission to be the destination for high quality ethically sourced multimodal datasets for next-generation AI models. The new capital will be used to grow Wirestock’s AI data platform, expand research capabilities, and develop tools to help content creators turn their work into income streams while providing premium training data to AI labs and hyperscalers. Formerly serving First and foremost as a way for photographers to get their photos distributed to stock platforms, Wirestock pivoted from the days of stock to becoming a major AI data infrastructure provider, now offering datasets to some of the world’s largest foundation model developers in a range of image video design asset, 3D, and audio formats. The firm announced that its creator base had grown to over 700,000 contributors around the world, uploading millions of creative assets and earning millions of dollars each month.
Also Read: IBM Unveils AI Delivery Model Focused on Real-World Enterprise Execution
The company claimed that the combination of the AI licensing trend and the impact of creator share has resulted in a 20x yoy increase in payouts to Wirestock creators and helped the firm reach over $40 million ARR. CEO and co-founder Mikayel Khachatryan said, “Wirestock has built an incredibly versatile platform that orchestrates the creation, curation, and delivery of complex multimodal datasets,” while emphasizing the company’s commitment to fair compensation, transparency, and responsible AI development. Unlike conventional approaches that rely on web scraping, the Wirestock platform distinguishes itself by purposefully creating and organizing its content for use in artificial intelligence algorithms through a combination of human and AI-powered moderation. This, according to investors, places Wirestock at the heart of the burgeoning multimodal AI industry, where there is an increasing need for high-quality and ethical datasets as artificial intelligence moves from text-based operations to more advanced visual and creative capabilities.