Moynihan adds, “Where possible, we will apply machine learning, other advanced automation capabilities and traditional process improvement methods, above and beyond RPA, to transform processes otherwise deemed too nuanced or complex.” An illustration of this can be demonstrated by studying one of the company’s recent engagements with a large telco provider in Australia. In this engagement, Eclair was able to combine ML with Robotic Process Automation (RPA) to interpret and take appropriate action on unstructured customer complaint inputs. This combination highlights how Eclair classified customer complaints and redirected them to the appropriate resolver groups using RPA. The client was receiving a significant number of complaints that required immediate action. Using some of the RPA techniques, Eclair successfully streamlined and classified the queries for quick resolutions. The use of ML algorithms further enabled them to implement a training model, with test data as an example, in turn, allowing the ML model to learn and understand the classification of complaints. This particular project substantiates Eclair’s approach of devising the right solution for the right opportunity to adequately fulfill the needs of its clients.

“We do not go to our clients stating that we can bring in ML or AI capabilities. We talk to them about their challenges, business processes, operational strategies and methodologies, and the opportunities for growth, cost reduction, compliance, customer experience or other improvement drivers,” adds Moynihan. Similar to the partnership with the telco provider, the asset management department of a client required the management of faults against rail fleet assets. Financial penalties were incurred when customer claims were not resolved within the service-level agreement (SLA) or, if and when they were identified as recurring faults. By adopting a combination of insights obtained from Eve and techniques of RPA, Eclair was able to identify recurring faults that occurred in real time and prioritized the resolution of the fault to the appropriate maintenance worker. As the implementation involved the utilization of ML algorithms, the company could also demonstrate trend analysis associated with faults, enabling preventive maintenance to avoid them.

Reinforcing Scalability, Customer Experiences, and Business Objectives

Eclair’s portfolio of product and service offerings not only enables the automation of business processes but also supports better client experiences, identifies potential revenue streams, and enhances the scope for scalability. “Our offerings enable organizations to scale their automation initiatives and help expand into new areas of opportunity while improving employee engagement and customer advocacy. This to us is a key differentiator that can support the transformation of an organization’s effectiveness,” explains Moynihan.

To further improve upon the value generated through its product portfolio, Eclair offers practical experience-based advisory services to enable and support clients in understanding the challenges, establishing operational structures, and ensuring the effective governance of automation strategies and virtual workforces. These offerings focus on taking a holistic approach to understanding the organization opportunities as a whole, as opposed to automating discrete opportunities within operational areas. By taking a more holistic view of the opportunities across an organization, Eclair’s portfolio identifies the areas and opportunities for improvement supported by automation, while highlighting the scope for higher efficiency. Collectively, the company’s portfolio of solutions and services cuts short the automation journey from a thousand miles to a few steps, assisting its clientele through their business endeavors.