Considering the importance of good customer service process, now companies are using chatbots which interact with the customer by audio or in the text formats. This artificial assistant provides customer with a memorable experience where consumer gets the solution for his concern promptly.
Volum.ai, a UK based Conversational AI and NLP solutions providing company, is the first company in global market to remove its traditional website and replace it with an AI-powered conversational platform ‘LUSY’. The company’s vision is to move the ‘search’ generation to the ‘ask’ generation by providing the ability for businesses to provide their customers, partners and employees with information, content, advice and support at the point of need. Volume.ai also has offices in the US and Sri Lanka.
Founded in 1997, Volume.ai has changed with the process by providing bespoke solutions and AI-related Consulting and Systems Integration services with two products inmarket. The first product is Big Brain Chatbot, which is a pre-built conversational platform. It is an independent to a particular NLP (Natural Language Processing) engine and can plug seamlessly into the major cloud-based NLP services from AWS, Facebook, Google, IBM Watson, Microsoft and Rasa. This enables customers to use their NLP service provider of choice rather than setting up a separate instance. The majority of customers will already have a preferred cloud services provider, so Big Brain chatbots can be quickly and cost-effectively added.
The second product is a first-to-market solution for helping chatbots developers and businesses using chatbots to better understand performance and the quality of the training data required to improve and scale the Chabot’s domain knowledge. QBox.ai visualizes the impact of making a change or addition to the Chabot’s NLP Data Model to ensure there is no regression in the model as a consequence. QBox is patent-pending and both applications are available as SaaS services.
Chris Sykes, the Founder & CEO of Volume.ai established the company with the vision that technology would rapidly permeate the sales and marketing operations of the future. As a futurist, Chris took the decision in 2015 to pivot Volume.ai towards Artificial Intelligence and looked at how it could be applied within a sales, marketing and customer experience context. Chris coined the term ‘experiential AI’ and has since built the three pillars that underpin EAI – AI-powered Conversational Platforms, Humanoid Robotics and Virtual, Mixed & Augmented Reality. He noted that as human Beings we intrinsically and continuously want to make our lives easier. In addition, he is also a regular speaker and panelist at AI events & forums and was a finalist in the ‘CEO of the Year’ category at the UK Private Business Awards 2018.
Comprehensive Strategy for Challenges
According to the company, last three years have thrown up many more challenges than the previous 18. The company’s services and modus operandi were very similar to the competitors that put Volume.ai into a market that was becoming commoditized and as budget and economic pressures came more into play, margins became tighter. The three core reasons to pivot the business were, to gain differentiation, to be able to penetrate multiple industry sectors and to become future-proofed. The first challenge was to change the way the market saw and 18-year-old business. It was then needed to show the market and wider market that Volume.ai was establishing itself as a key player in the emerging AI space. And it also had credibility and capability beyond the raft of new competitors whether these were start-ups or the grand global application vendors. The first move was to replace company’s .com site with an AI-powered conversational platform. In November 2017, Volume.ai launched LUSY to the market. Volume.ai were the first company in the world to do that and in doing so, it discovered other areas to exploit. The strategy was to use best-of-breed AI services and to blend them with the own IP. The company didn’t want to be tied to any technology or vendor, so it experimented with many. Working within NLP and building NLP Data Models that power ‘intelligent’ chatbots, it came across one of the key barriers to chatbots success and adoption. This understood how the chatbots performed and how it performed after any retraining or training took place. The company took the decision to address this issue head on and thus ended up with another first-to-market, Qbox.
Promoting New Technology
The world of AI is very different to the world of technology. AI is not an application but an ecosystem of services. Right now, there is a lot of hype and confusion around what AI is and which facets are relevant to a business today. A lack of knowledge is the main barrier to accessing and adopting AI-related solutions. Volume.ai is technology and vendor independent, which presents an unbiased view on AI and the AI market. Using unique IP, the company run AI workshops, called EXPLAIN Workshops to educate a business’ stakeholders on how to view, assess and adopt AI with their organization. With this new-found knowledge, the stakeholders can think about potential use cases and where they might be applied in the enterprise or indeed, outside the enterprise. Once a use case or use cases have been validated to be able to deliver a quick win, Volume.ai co-develops with the customer. It is important that businesses approach AI solutions iteratively and that their existing resources may change in the future.
Aiming to get Advance
According to Volume.ai, the use of technology will become more ubiquitous and with advances in user experience, easier to use. Technologies such as facial, gesture and speech recognition will eliminate the need for devices such as mice, keyboards and other input peripherals. The linear data sets of the past will be replaced by new data sets based on a physical interaction or dialogue between human and smart machine. Volume.ai aims to remain at the forefront of these emerging technologies and is already scaling its resources to support new and emerging tech roles such as NLP Data Model Analyst, Dialogue Author, Behavior Scientist and NLP Data Model Developer.