AI-powered Helpdesk Support
Client background and business context
Client profile: Companies active in either financial services, manufacturing, or retail industries.
Proposed solution: RPA- and conversational-AI-based helpdesk support.
Growing businesses with a proportionally expanding customer base that demand ultra-fast yet highly professional customer support services may find themselves plagued by emerging issues, such as a growing number of customer support requests, long resolution times and lost issues, frequent customer issues that demand large volumes of time-consuming manual work, and increased difficulty in keeping track of assets, to name a few.
Conversational artificial intelligence (AI) is a new IT paradigm that is slowly taking over the way we consume (and expect to consume) technology and, ultimately, any technology-infused product or service. Given this evident evolution powered by modern IT technologies – RPA, AI, ML – future human–computer interaction models will inevitably involve virtual characters supporting both enterprises and end users.
We aim to understand exactly what challenges need to be solved for our clients to move forward quickly and to be better suited to the fast-paced business world we’re in today.
Enter Elli-AI, a multichannel, outcome-driven virtual agent that acts as an expert human-like interface to enterprise operational systems, quickly and consistently solving service tasks at scale. Its mission: both internal and external positive impact on engagement, cost reduction, and a company-wide boost in efficiency and speed as well.
Our projects start with a discovery workshop, at the end of which strategic goals and objectives are laid out. We understand where our client’s focus is for the next month, the next quarter, the next year, and how we, with the help of Elli-AI, can best enable them to do their best against their competitors, as well as for their customers.
We provide a thorough ROI analysis of the proposed digital solution, Elli-AI, our virtual assistant developed in-house and specifically programmed to meet our client’s business needs. Decisive KPIs are specified as well.
Having all this information, we can move on to fully determining the solution: the solution scope, a prototyping roadmap, as well as an estimate of the production timeline and the necessary investment.
Next, we’re ready to develop the prototype as planned. We assess the results and adjust priorities if necessary.
We stay on the project for post-launch monitoring and optimisation to ensure that the solution is exactly what our client needs to perform better, whether internally or externally. We monitor the established KPIs, optimise the solution accordingly, and adjust KPIs if necessary.
Our aim is to be both efficient and effective in responding to our client’s challenges and concerns: we employ technical and business know-how in order to provide our clients with the right digital solutions, optimally designed and developed to fit their business needs perfectly.
Multichannel implementation: One size does not fit all, but however your business processes may work, our RPA- and conversational-AI-based solution can fit any flow or platform.
24/7 Support: Elli-AI never sleeps – while your company benefits from round-the-clock, end-to-end processing, your customers will be happy to benefit from 24/7 customer support, with significantly reduced wait times.
Knowledge base: Benefit from an easily updatable, easily accessible, always useful knowledge base your employees can enter for their FAQ.
Thinking Elli-AI – our in-house-developed virtual assistant – may be just what your company needs to improve performance and customer satisfaction? Contact us for an AI maturity assessment, and let’s find out!
Self-service setup: Elli-AI can take on simple tasks – like password resets – all on its own.
Fast and accurate processing: Rely on our in-house-developed virtual assistant to become a great aid to your employees by always suggesting suitable solutions to the challenges they encounter, while taking on the task of auto-classifying issues and routing them accordingly.
Other use cases: