EXPERIENCE DESIGN FOR NATURAL LANGUAGE INTERACTIONS
Mphasis conversation interfaces for cutting-edge user experiences
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About Mphasis
As new UI paradigms become the order of the day, user focus and the need to design experiences that are relevant to the user remain paramount.
At Mphasis, we realized the importance of leading with design early, even in newer technologies like conversation user interface (CUI). To address this need, we developed a custom conversational design methodology (based on user-centered design methodology) aimed at modeling and designing CUIs with relevant artifacts. Our solution enables organizations to take a design-led approach to natural language interactions resulting in more mature and user-focused customer experiences.
Also, our accelerators significantly shorten the supervised learning phase and go to market (GTM). Our IP and frameworks allow for the definition of an experience that puts the system ahead of the game as compared to having to wait for data collection and analytics for the self-learning aspects to kick in.
We firmly believe that as technology provides multi-channel and multi-format access to information, structuring that experience through informed, user-centered, and collaborative design processes is the only way to ensure that (regardless of channel) users accomplish their tasks quickly, easily, and intuitively.
Ability to learn about people’s needs and their emotional context, to be able to design personalized conversations.
Capability to understand language design challenges and leverage fundamental design, best practices, and conversation design to customize the need for a CUI.
Usage of a well-defined process and a conversation design modeling template, which can quickly capture information about sample utterances, intents, and entities.
Leads to Faster Go To Market (GTM) with a More Mature Product
Designed to Work with Any Off-the-shelf Product and Can Be Coupled with Custom Builds
Drives Shortened, Supervised Learning of the Final Product through Mphasis Accelerators