SAN FRANCISCO — Lang.ai has completed a $10.5 million Series A round led by Nava Ventures with participation from new and existing investors including Oceans Ventures, Forum, Flexport Fund, as well as industry leaders – Mike Murchison (CEO of Ada), Joaquim Lecha (CEO of Typeform) and Javier Mata (CEO of Yalo), senior engineering and sales leaders at pioneering AI-based companies including Google, Weights & Biases, Looker, and Ocrolus.
For high-growth brands, scaling customer support has never been harder, yet never more important. The pandemic has increased the breadth of support required by brands while the great resignation has made finding the talent to service those even more difficult.
Through the applications of Lang’s technology, CX teams are able to scale more efficiently. Lang automatically tags every customer conversation in real-time. By tagging each ticket, companies are enabled to extract more granular insights about their client interactions and more intelligently resolve their issues through easy-to-deploy automation rules. Existing customers include Stitch Fix, Ramp, Good Eggs, Novo, Petal Card, Hippo Insurance and Pair Eyewear.
Lang’s automation is connected to existing help desk solutions such as Zendesk and Intercom. It requires no code and no technical resources to get started. It’s a low lift, high impact solution to tap into the growing amount of data and automation potential for customer service teams.
Some real-life customer examples include Fintechs routing tickets to their Product Operations team when launching new products, E-commerce brands automatically escalating canceled orders to reduce fulfillment costs, and brands auto-responding to zero-touch tickets via email for issues where an agent doesn’t need to be involved.
Across all these use cases, Lang helps CS teams scale. Ramp is one example of this, as put by Tony Rios, Customer & Product Lead at Ramp; “When we onboarded Lang, we were a team of 2 support agents, including myself, and just setting up our Zendesk instance to our needs. While we’ve scaled the business massively over the past year, we’re always thinking through how we scale operationally without throwing more people at the problem. Lang is able to handle many of the most time-consuming tasks like tagging, routing to the right team of agents and handing playbooks to our agents.
“Lang’s mission is to empower anyone to benefit from the power of AI, and we’ve taken a different approach tailored for business users and done visually, instead of via traditional machine learning approaches that rely on large data sets and labeling/training,” says Jorge Penalva, CEO of Lang.