Lang.ai, which has developed a no-code platform for businesses, closed on a $ 2 million seed funding round.
The company’s SaaS platform allows custom users to create any free-text data through a drag and drop interface based on AI-extracted concepts.
Village Global led the financing, which included participation from new and existing backers Acceleprise, Oceans Ventures, Alumni Ventures Group, 2.12 Angels, GTMFund and Lorem Ventures.
Spain-born Jorge Penalva founded Lang.ai in 2018 with the goal of giving “the ability to create enterprise-ready natural language processing models in just a few minutes” to any user. It was created to give non-engineers a way to automate repetitive tasks in use cases such as customer service and claims processing.
“It can be set in our clouds or theirs,” Penalva said.
Lang.ai saw its revenue double from the last quarter of 2020 to the first quarter of 2021, and seed financing was primarily driven to continue this momentum.
“We are demanding as projects with our larger customers, so we needed funding to be able to support that demand,” Penelva told TechCrunch.
In his previous role as CEO of Sennatisis, Penelva realized that processes driven by free-text data remain a blind spot for many companies.
“Today, millions of dollars and hours are invested by companies to manually read and process text information captured from heterogeneous areas of their business,” he said.
His mission with Lang.ai is to “empower businesses to make AI work for them without the technical complexities of building and training operations.”
Specifically, Penalva stated that Lang.ai’s product analyzes customer historical data “in minutes” and suggests building AI-extracted concepts Custom categories via a drag and drop interface. Custom categories are implemented to automate “tedious” tasks, such as manual tagging and routing support tickets, processing insurance claims and sending field engineers for incoming work order requests.
Simply put, Lang.ai aims to remove the technical burden of implementing AI for a business.
The Lang.ai community of users (called “citizen NLP builders”) mostly hold non-technical business roles, ranging from customer service operations to marketers, business analysts, and UX designers.
Customers include Freshly, UserZoom, Playvox, Caxbank in Spain, Yellow Chat and Bancombombia.
Freshly, director of infrastructure efficiency Ben Segal called the stage “so agile”.
“Out of the box, it took us two days to create automated tagging, 15% more reliable than the previous platform that we had in production for 2 years, with the added benefit that all our teams now support us Can tap and exploit data, “said Sehgal.” The marketing team has built workflows to understand key customer moments. Our data and analytics team is super excited about having all these new tags in Snowflake, and It’s crazy how easy it is to use.
Penalva is proud of the fact that Lang.ai’s engineering team is primarily based in Spain and is capable of developing a 10-man company outside its country of origin.
“With very few resources, it took us a while to build an enterprise-grade product and find the right set of initial customers and investors,” he said. “I moved from Spain to the US to build a global company and this is just the beginning … Lang has always been driven by the immigrant hustle, and it has been important to our values since day 1.”