Service Co-Pilot uses a ChatGPT plugin to generate recommendations sourced from historical service data and data synthesized from the knowledge of an organization’s subject matter experts. This innovative approach allows the engine to predict the best solutions to even the most complex customer service issues, empowering every stakeholder (e.g., the end customer, contact center agent, field technician, or service leader) to diagnose and resolve problems like an expert. The omnichannel platform can be leveraged, via desktop, mobile app, or chat, at every touchpoint across the customer experience.
“Service organizations are challenged with hiring and retaining skilled service professionals while managing rising customer expectations and sky-high costs. One in three service calls result in a truck roll, which can cost upwards of $2,500 – this is no longer sustainable,” says Assaf Melochna, President and Co-Founder of Aquant. “Generative AI can reduce these costs and bridge the customer experience gap. To help organizations keep pace with these changes, Service Co-Pilot is enabling users to access critical information without escalating an issue. This helps alleviate the strain on the service workforce so organizations can exceed customer expectations.”
Service Co-Pilot’s unique approach to AI
Service Co-Pilot combines Aquant’s proprietary technology with open foundational models. With ChatGPT alone, customer service professionals will have difficulty relying on answers due to the risk of hallucinations and challenges with more advanced troubleshooting scenarios. However, Aquant’s AI technology goes further. First, it mines structured and unstructured service data, including work orders, machine logs, service manuals, and free text notes using a service domain-specific natural language processing model. Then, it improves AI performance by datafying expert knowledge – the process of converting the knowledge stored in the minds of your experts into synthetic data.
This approach trains Service Co-Pilot over time, making it a best practice machine that can adapt and adjust based on real-world feedback, rather than relying on hard-coded workflows that may not be optimized for all scenarios. Aquant’s internal data shows that incorporating human expertise is critical: 30% of solutions are not found in historical service data, but are found in the data provided by experts. By tapping into the knowledge of subject matter experts, Service Co-Pilot achieves more personalized and reliable results.
Service Co-Pilot’s New Features: Search and Self-Service
Service Co-Pilot’s generative AI search feature allows stakeholders to ask a chatbot for the right answers to any service question, at any time. This feature helps users solve specific customer issues and provides guidance along with useful links to the exact point in manuals where the answer exists. If more than one answer exists, the user will be asked a series of questions generated by AI to triage the issue and narrow down the most viable and cost-effective solutions.
In addition to the search feature, Service Co-Pilot includes new self-service capabilities. So now, end customers – in addition to technicians and contact center agents – can make intelligent, informed decisions using Self-Service Triage or Intelligent Triage, Service Co-Pilot’s troubleshooting and diagnostic tools.
Additionally, the platform includes Service Insights, an analytics dashboard built for service leaders to access clear, detailed, and holistic recommendations to improve workforce performance, customer risk management, and product quality trends.
“Leading organizations are increasingly shifting toward low-touch, more efficient customer experiences. In service, we call this approach shifting left,” said Shahar Chen, CEO and Co-Founder of Aquant. “Aquant’s Service Co-Pilot helps organizations reduce costs and the time it takes to solve cases. This technology is no longer optional for organizations that want to survive long-term.”