Zinier raises $90 million to embed field service work with AI and machine learning

It’s anticipated that workplace automation tools will see an uptick in adoption in the next few years. One company leading the charge is San Francisco-based Zinier, which was founded in October 2015 by Andrew Wolf and former TripAdvisor market development manager Arka Dhar. A developer of intelligent field service automation, the startup provides a platform — intelligent service automation and control, or ISAC — aimed at fixing machinery before it breaks and maintaining mission-critical client services.

After raising $30 million across three funding rounds, the first of which closed in January 2016, Zinier is gearing up for a major expansion with fresh capital. It today announced that it’s raised $90 million in series C financing — nearly quadruple its series B total — led by new investor ICONIQ Capital, with participation from Tiger Global Management and return investors Accel, Founders Fund, Nokia-backed NGP Capital, France-based Newfund Capital, and Qualcomm Ventures. The tranche brings Zinier’s total raised to over $100 million, and CEO Dhar says it’ll support the company’s customer acquisition strategy and accelerate the expansion its services across telecom, energy, utilities, and beyond.

Specifically, Zinier plans to expand in the Asia Pacific, Europe, and Latin America regions, particularly Australia and New Zealand. And on the R&D side, it’ll build out its AI technologies at the platform level and partner with global system integrators.

Above: Zinier: Scheduling and dispatch

“Services that we rely on everyday — electricity, transportation, communication – are getting by on centuries-old infrastructure that requires a major upgrade for the next generation of users,” added Dhar. “A field service workforce powered by both people and automation is necessary to execute the massive amount of work required to not only maintain these critical human infrastructure, but to also prepare for growth. Our team is focused on enabling this transformation across industries through intelligent field service automation.”

Zinier’s eponymous suite delivers insights, general recommendations, and specific tasks by running operations metrics through proprietary AI and machine learning algorithms. As for ISAC, it triggers preventative actions based on equipment health while anticipating stock transfers, and it scans technicians’ calendars to help define ongoing and potential problems. A separate component — Zinier’s AI configurator — affords control over the recommendations by enabling users to define the corpora on which the recommender systems are trained, and to set the algorithms used.

A complementary workflow builder automates routine tasks with custom workflows, and it lets users build, deploy, and update those workflows to their hearts’ content without having to write custom code. They’re also afforded access to the app builder, which supports the building of custom solutions for specific field service problems, as well as the grouping together of key functionalities into a single bundle that can be deployed across teams (subject to roles and permissions).

Coordinators can accept or reject suggestions on the fly — the former sets off a series of automated actions. And managers can build custom dashboards from which teams can view insights generated by the analysis of historical trends, and optionally receive proactive alerts configured to address particular pain points like when a task is at risk of falling behind.

Zinier supports scheduling and dispatching so that technicians know their work orders up to months in advance, and it autonomously determines general capacity based on transit time, technician availability, and task prioritization. Elsewhere, with AI, Zinier attempts to predict systems failure by weighing real-time internet of things data against historical trends, and it tracks and manages inventory to ensure technicians consistently have the parts they need.

On the mobile side of the equation, Zinier’s app makes an effort to boost productivity and job satisfaction by ensuring accurate job completion — in part by surfacing contextual and back-office data for technicians in the field. Service workers can access not only relevant documents, but detailed site records and readings from internet of things gadgets.

As my colleague Paul Sawers notes, field service organizations are embracing AI and machine learning at an accelerated pace — and startups are rising to meet the demand. There’s the well-funded ServiceMax, which was acquired by GE Digital a few years back for $915 million and which in turn sold a majority stake to Silver Lake in December 2018. Salesforce also offers a product called Field Service Lightning, while Microsoft snapped up FieldOne Systems in 2015 and now offers a field service management platform called Dynamics 365 for Field Service. For its part, Oracle in 2014 acquired the reportedly lucrative TOA Technologies, and in 2018 SAP bought AI-powered field service management company Coresystems.
Zinier’s ostensible advantage is that its AI-powered platform was developed in-house, from the ground up, and that it isn’t distracted by other business interests. “For Zinier, field service is our sole focus,” Dhar told VentureBeat in an earlier interview. “The platform has allowed us to quickly build Field Service Elements, our end-to-end field service automation product. And as we continue to build our expertise in different industries, we can quickly configure specific use case solutions for customers.”

Source: Read Full Article