Idibon

Idibon was a San Francisco-based startup founded in 2012 by Robert Munro and Tyler Schnoebelen. The company focused on providing insights from language data through natural language processing (NLP) and data science. The founders' backgrounds are rooted in linguistics and technology; Munro's work in adapting machine learning for low-resource languages for healthcare and disaster response was a key motivator for the company's mission. This was complemented by his experience at Stanford, where he and Schnoebelen co-authored a paper on crowdsourcing linguistic annotations.

The firm's core business involved transforming unstructured data, such as emails, social media, and websites, into structured insights for business intelligence. Idibon served a range of high-profile clients across various sectors, including finance, healthcare, automotive, and gaming. For instance, it helped a major smartphone manufacturer become smarter in more languages and was the preferred vendor for social media analytics for a large auditing company. The business model centered on its proprietary technology that combined human and machine intelligence to deliver highly accurate text analytics services. The company's Idibon Studio and Idibon Terminal products allowed clients to filter, classify, and analyze text data, with adaptive learning capabilities that improved accuracy over time.

Idibon's platform was designed to be language-independent, a significant differentiator that allowed it to support over 60 languages, including those with fewer than 100,000 speakers. This was a direct reflection of its founding mission to bring language technologies to all the world's languages, addressing the reality that most digital communication is not in English. The technology supported functionalities like sentiment analysis, text categorization, and entity recognition. Over its lifetime, Idibon raised a total of $6.9 million in funding over two rounds from investors including Khosla Ventures, Altpoint Capital Partners, and Samsung. The company's assets and intellectual property were eventually acquired by undisclosed buyers, and the company is now considered deadpooled.

Keywords: text analytics, natural language processing, NLP, data science, machine learning, unstructured data analysis, sentiment analysis, business intelligence, language technology, multilingual data processing, computational linguistics, text classification, entity recognition, human-in-the-loop, Robert Munro, Tyler Schnoebelen, Khosla Ventures, social media analytics, customer feedback analysis, market intelligence, text mining