Customer support automation platform Aquant raises $70M

Aquant, a platform leveraging AI to help customer support staff, at present introduced that it closed a $70 million collection C funding spherical led by Qumra Capital, Perception Companions, and Pitango Development with participation from Lightspeed Enterprise Companions and Angular Ventures. The capital brings the corporate’s total raised to this point to $110 million, and CEO Shahar Chen says it’ll be used to bolster product improvement and increase Aquant’s engineering, shopper companies, and go-to-market groups with positions within the U.S., Europe, and Israel.

Customer support groups are more and more embracing AI and automation because the pandemic continues to place a pressure on day-to-day operations. According to Gartner, 37% of service leaders are both piloting or utilizing AI bots and digital buyer assistants, whereas 67% consider they’re high-value instruments within the contact heart. Early adopters of AI options report a 25% enchancment in buyer expertise and accelerated charges of innovation, in addition to larger competitiveness, larger margins, and higher worker experiences, IDC reports.

New York-based Aquant, which was based in 2016 by Chen and Assaf Melochna, goals to present service leaders, reps, and groups data they want proactively and on-demand. Aquant transforms unstructured information into structured information after which predicts the options for service challenges.

Above: Aquant’s dashboard.

Picture Credit score: Aquant

“By offering deep evaluation of an organization’s service information, Aquant is ready to current a full-body well being report that reveals strengths, weaknesses, and alternative for enchancment,” Chen informed VentureBeat through e mail. “The platform supplies a transparent map of a service group. The identical service information additionally helps to supply particular service suggestions, serving to subject engineers repair the foundation explanation for the issue accurately the primary time. From an govt standpoint, Aquant helps direct service leaders the place to look, present them what wants consideration, assist them prioritize, assist them develop coaching plans — all which finally result in higher, extra magical service.”

Making sense of knowledge

There’s a protracted checklist of widespread challenges within the customer support trade, notably in subject service. In a 2018 survey, the largest concern for managers is guaranteeing that their subject workforce is working at optimum effectivity and productiveness. An estimated 66% of the workforce makes use of data bases — e.g., on-line FAQs — in contrast with 82% of shoppers. That’s why 70% of service organizations consider they’ll be burdened by the data lack of a retiring workforce within the subsequent 5 to 10 years, the Service Council reports.

Aquant seeks to handle the problem by mining information from varied sources to study manufacturing, utilities, and telecom corporations’ distinctive service languages. At a excessive stage, the platform captures the data of subject-matter consultants by extracting insights from information silos like buyer relationship administration platforms and enterprise useful resource planning software program. Based on Chen, Aquant takes solely days to study a service language from thousands and thousands of buyer tickets, components catalogs, stock, provide chains, web of issues alerts, and extra.

Aquant’s AI algorithms establish patterns and make choices as they interpret the variations in the way in which that service points are described. The platform then extrapolates context and intent and maps issues to options because it prioritizes technicians’ job schedules based mostly on enterprise targets. For instance, Aquant can predict when buyer complaints are the results of error or environmental components versus product failure. Furthermore, the system can mechanically immediate group members to reply, recommending options based mostly on cost-effectiveness whereas trying to find anomalies in guarantee claims.

“[Our] platform … maps out all the things from worker efficiency to half and asset efficiency and may create real-time buyer threat alerts. Managers, administrators, and VPs can now see very clear connections between their group and repair efficiency ranges and the way these components contribute to service outcomes,” Chen defined. “[We also provide] clever triage, which transforms tribal data into prescriptive intelligence, enabling name heart brokers and subject techs to troubleshoot issues. A buyer explains the issue and solutions a couple of brief further questions, and our AI then recommends the most definitely or most cost-effective resolution for the issue.”

Aquant just lately launched Service Insights, a software that gives a window into components that influence buyer experiences in addition to suggestions, trade benchmarks, traits, workforce efficiency stats, buyer threat scores, and coaching methods. And in August, the corporate rolled out Clever Guarantee Audit, which categorizes information to assist guarantee managers course of or reject “high-risk” claims.

“Our clients — service executives — face a serious downside: a scarcity of expert labor. This downside is the results of an getting older workforce, a scarcity of curiosity within the expert trades by youthful generations, larger turnover of Millennial and Gen Z staff, and the acceleration of the labor scarcity brought on by the pandemic,” Chen continued. “Service leaders battle to seek out and retain certified service technicians, and, because of this, the standard of service and buyer experiences undergo. Aquant provides an answer that captures and disseminates the data of our shoppers’ most expert staff — in order that new and underperforming staff can have the data to supply nice service experiences each time.”

Aquant’s rivals within the international customer support automation market embody Zendesk-backed Cleverly.ai, Kustomer, Directly, Zinier, and to a lesser extent TechSee and CareAR. However the firm has managed to carve out a distinct segment for itself, with over 30,000 customers throughout clients together with The House Depot and Siemens Healthineers in industries together with medical gadget, meals gear, capital gear, and industrial automation and equipment manufacturing.

“Probably the most frequent aggressive determination we face is that many service organizations are trying to construct their very own AI platforms in-house, however that may typically take a number of years and require a complete group of knowledge scientists, analysts, and IT integrators,” Chen mentioned. “Plus, they lack the historic data from different Aquant clients that’s constructed into our information algorithms. Aquant’s AI components in trade data and information and combines that with a service firm’s information, which signifies that our outcomes are in a position to present options based mostly on a bigger dataset and trade context.”

Aquant at present has 90 staff and expects to have over 120 by the tip of the yr.