Applied Labs co-founders Soham Waychal and Michael Woo
Don’t believe the hype. That’s the message from Michael Woo, the founder of New York-based start-up Applied Labs, who warns that many of the claims currently being made for the success rates of artificial intelligence tools in customer services are overblown. His business, which is today announcing it has raised $4.2 million of seed funding, wants to cut through such hyperbole.
“I’m pretty sceptical about some of the customer resolution rates that we see well-known providers make for their AI solutions,” says Woo. “Their definitions of what constitutes resolution for a customer are often over-inflated; if you talked to the actual customers, you would very often find they weren’t particularly satisfied.”
AI certainly has the potential to help enterprises serve their customers much more effectively, Woo believes. From chatbots that respond to customer inquiries more quickly than human call agents to agents that pull customer data from every part of the business, AI can drive genuine improvements. The problem, however, is that many of the tools currently available aren’t delivering on this promise; getting them up and running is challenging; iterating them for improvement is tricky.
“The bottleneck is no longer the model: quality, speed and cost have reached an inflection point where almost every business can save time, money and improve the quality of their support,” says Woo. “The challenge is in the data, tools and platform for teams to easily set up and perfect AI agents on their business-critical workflows.”
Applied Labs therefore takes a slightly different approach. “You get the best results when AI efficiency is combined with human judgement,” Woo explains.
In practice, the Applied Labs solution spans three components. First, its service offers an AI agent that can work across all the channels through which enterprises interact with their customers – chat, email and phone. Second, it offers an orchestration tool that enterprises use to set up their AI agents so they integrate with the business’s data and workflows. And third, it offers evaluation tools to test, audit and monitor the outputs from the technology – to mark the organisation’s work, in other words.
Critically, the platform incorporates built-in escalations that automatically bring humans into the loop where necessary. The evaluation data also provides the business’s leaders with a means by which to judge its success. “AI allows you to scale up your best human judgement on an infinite volume of tasks, but human judgment is still necessary to get the best quality results and handle edge cases,” adds Woo.
Will this solution work better than rival AI platforms for customer service teams – including some of the offerings from the biggest names in customer relationship management software, many of which are making bold claims about the quality of their own solutions? Woo is convinced the platform’s results will speak for themselves. “We provide more insight, with metrics that offer more honesty and visibility about what AI is really resolving,” he says.
The early signs are good for the company. Launched last February, Applied Labs has already signed up around a dozen customers, with revenues growing quickly. Woo points to his experience at Scale AI, the high-growth AI start-up, where he was an early-stage employee and led a team focused on operational scalability. Woo’s co-founder Soham Waychal also has a track record of success in the sector, having led engineering at the ecommerce specialist Canal.
Investors are optimistic that Applied Labs can break through in a crowded space. Today’s funding round is led by Abstract, with participation from Point72 Ventures, Outlander and Tetra, as well as a number of angel investors. The round takes the total amount of money raised by Applied Labs to $5.2 million.
“Few founders truly grasp the operational intricacies of deploying AI in mission-critical workflows,” says Ramtin Naimi, founder and general partner at Abstract. “Applied Labs’ commitment to pairing trust with capability, underpinned by their human-in-the-loop approach, is precisely what enterprises need to confidently embrace AI-powered customer support.”
