Coactive AI: Helping Machines Understand Visual Content, Revolutionizing Data Analysis

In today’s data-driven world, businesses are increasingly relying on data to make informed decisions. However, many companies face a significant challenge: understanding the vast amount of unstructured visual data they possess. Coactive AI, founded by Cody Coleman ’13, MEng ’15, and William Gaviria Rojas ’13, aims to solve this problem with its innovative AI-powered platform.

Coactive’s platform is designed to analyze unstructured visual content such as images, audio, and video, enabling businesses to unlock valuable insights. By instantly searching, organizing, and analyzing this data, companies can make faster and more effective decisions.

Coleman explains that while businesses have become proficient in extracting value from structured data like tables and spreadsheets, unstructured data, which accounts for 80 to 90 percent of the world’s data, remains largely untapped. He believes that AI is crucial for processing visual and audio data at scale, marking the next phase of the big data revolution.

Coactive is already collaborating with major media and retail companies, helping them understand their visual content without the need for manual sorting and tagging. This allows them to deliver relevant content to users more quickly, remove inappropriate content, and gain insights into user behavior.

The founders envision Coactive as a tool that empowers humans to work more efficiently and tackle new challenges. Coleman emphasizes the importance of humans and machines working together, stating that AI has the potential to either unite or divide us. Coactive aims to be an agent that fosters collaboration and enhances human capabilities.

Coleman and Gaviria Rojas met through the MIT Interphase Edge program and later collaborated on bringing MIT OpenCourseWare content to Mexican universities. This experience sparked Coleman’s entrepreneurial spirit and led him to explore the power of AI at MIT’s Office of Digital Learning.

Coleman’s work at MITx, where he used machine learning to study human learning, further solidified his interest in AI. He realized the potential of AI to democratize education and create personalized learning experiences. After MIT, Coleman pursued his PhD at Stanford University, focusing on lowering barriers to AI adoption. This led to collaborations with companies like Pinterest and Meta, where he gained insights into the future of AI and content.

Gaviria Rojas, who worked as a data scientist at eBay, shared Coleman’s vision for unlocking the potential of multimodal data through AI. Together, they recognized the need for a technology that could process images, video, audio, and text at scale.

The resulting platform, described by Coleman as an “AI operating system,” is model-agnostic, allowing for continuous improvement as AI models evolve. Coactive’s platform includes prebuilt applications that enable businesses to search content, generate metadata, and conduct analytics.

Coleman emphasizes that AI is enabling machines to “see” the world as humans do, blurring the lines between the digital and physical realms.

Reuters, for example, uses Coactive to enhance its image database, enabling journalists to quickly find relevant photos using AI-powered search. Fandom, a large online platform for TV shows, video games, and movies, uses Coactive to moderate content and remove inappropriate material more efficiently.

Coactive’s founders believe that their technology is ushering in a new era of human-computer interaction, where humans can interact with machines more naturally and intuitively.