Wirestock, a platform initially known for helping photographers distribute their work to stock services, has successfully secured $23 million in Series A funding. This investment marks a significant milestone in the company’s strategic pivot towards becoming a leading provider of creative multimodal data for artificial intelligence laboratories. The funding round was spearheaded by Nava Ventures, with additional participation from SBVP (co-founded by Sheryl Sandberg), Formula VC, and I2BF Ventures. This capital injection brings Wirestock’s total funding to approximately $26 million.

The company’s transformation in 2023 saw it transition from a stock photography facilitator to a dedicated data supplier, offering datasets encompassing images, videos, design assets, and gaming and 3D content to AI labs. Wirestock reports a network of over 700,000 artists and designers who contribute to data collection efforts. Mikayel Khachatryan, co-founder and CEO, emphasized the transparency of this shift, noting that the majority of artists from their previous model opted to become data providers for AI. Khachatryan revealed that the company currently boasts an annual run-rate revenue of $40 million and has already distributed $15 million to its contributors.

The demand for high-quality data supply services is rapidly escalating as AI labs worldwide compete to refine and advance their models. Wirestock currently supplies multimodal data to six major foundation model makers, though their names were not disclosed. The company aims to specialize in providing data for AI models geared towards creative applications, such as image and video generation, and is also exploring modalities like audio and music. Freddie Martignetti, founder of Nava Ventures, highlighted his firm’s interest in data procurement innovation, stating that Wirestock possesses a deep understanding of what foundational models require for developing more human-like AI systems. The newly secured funds will be allocated towards expanding research, engineering, and product teams, as well as developing enterprise software for AI labs to collaborate on datasets.