Understanding these conversations via natural language understanding (NLU) unlocks a myriad of use-cases across call-center AI, business automation, chatbots, and conversational analytics
And while training and deploying state-of-the-art NLU models is quickly becoming a commodity (thanks to advances in cloud computing and services), the crux of the problem now lies in managing the data that powers these models at scale, and increasing the coverage and accuracy of the model with the long tail of data.
HumanFirst allows teams to build and curate highly accurate training datasets for natural language understanding (NLU) models, at a fraction of the time and cost it otherwise takes.
Product, machine learning and data labeling teams use HumanFirst to centralize all their raw conversation data (from support, sales and product communication channels), transform it into training data, and continuously improve the performance of their NLU models.
More than 600 teams signed up in the six (6) months following the launch of their beta, including the world’s leading call centers, fintechs, insurance, and AI development companies.
Built by the same product engineering team behind PasswordBox (acquired by Intel), HumanFirst is positioned to unlock a new wave of NLU capabilities across verticals and industries.
