Virtual assistants, digital assistants, chatbots, voicebots, conversational AI. No matter the name, deliver a human-like, interactive customer experience on 30+ messaging channels
Decipher free text or natural speech based queries using pre-trained Natural Language Understanding (NLU) engine
Recognize new and ambiguous requests and classify in pre-trained categories to create an intelligent dialogue
Comprehend user’s mood and classify into positive, negative or neutral. Identify best course of action and bring in human agents if needed
Get tweet sized FAQs automatically by ingesting product descriptions, images, blogs and T&Cs
Generate numerous sentence variations with a few base statements
Process vernacular queries in 30+ languages without having to re-train the AI on every language.
Aid decision making with relevant product recommendations and a search-like conversational response
Deliver a smooth experience by retaining context even with complex, mid-way subject switches
Allow users to switch modalities, and respond in real-time using automated speech recognition
Ready to use intent library for banking, financial services and retail
Integrate AI with leading CRMs, commerce platforms, support tools, ERPs, payment gateways and more
Leverage AI to automate inbound call answering, and save on operations cost
Go truly omnichannel with AI on 30+ messaging, voice, and video channels
Build and tweak your journeys with a self-serve, drag and drop journey builder
Go-live in shortest time, with best-in-class 93% out-of-the-box AI accuracy
Make online finance easy with AI and 150+ finance intents that automate routine customer interactions across banking, lending, insurance and more - securely and at scale.
Make it super convenient for your users to access services such as Mutual Funds, SIP, Credit Score check, insurance policy purchase and claims settlement.
Deliver expert guidance anytime, anywhere, and sell more with a personalized and easy-to-navigate shopping experience on chat.
Create a direct relationship with your customers, share product information, usage directions, ingredients and more by linking QR codes on packaging and other entry points
Understand unique requirements and preferences of each customer and propose tailored packages. Increase bookings with personalized deals and offers.
“Gupshup is special for its high AI and ML competency and has strong understanding of the fashion retail business.
We get deep insights on customer behavior and decision-making process, and can provide much better service.”
“By leveraging the power of conversational AI, the Keya chatbot is available across digital channels such as the Kotak website, internet banking, 811 and the Kotak mobile app”
Conversational AI is a technology that enables machines to converse with humans in natural, human-like language. With this technology, chatbots, virtual assistants, voice bots, etc., can understand and process human language inputs and respond smoothly to them and with the correct context.
With conversational AI, businesses can create user-friendly chatbots and voice assistants that allow customers to interact with the brand in natural language, in real-time. Businesses can not just connect with customers in relevant and meaningful ways, but also learn from these interactions.
FAQ Automation is a process where the AI engine generates bite-sized questions and answers using minimal inputs. It consumes collaterals such as policy pages, websites, help pages, product descriptions and manuals.
Conversational AI-based digital assistants are different from rule-based and scripted chatbots in the sense that a traditional chatbot has pre-coded responses to anticipated consumer queries, whereas digital assistants driven by conversational AI techniques can decipher a consumer's true intent even if the query is not phrased properly. It can maintain a conversation with a level of understanding similar to human agents.
Domain-specific AI goes deep into the conversational aspects of a particular industry. For example, there are industry-level terminologies such as 'Rate of interest' in banking or '7 days return policy', and 'size issues' etc. in retail. AI needs to understand these aspects to provide a human-like experience to users.
Let's say you are hiring for a relationship manager role and have two candidates. One candidate has a lot of experience but is not from your industry. But, the other candidate has both experience and comes from the same industry you operate in. Whom will you hire?
In the same way, domain-trained AI understands the context better and can have more meaningful conversations. Pre-built journeys cater to specific use cases of a particular industry, e.g., KYC in banking, Credit score check in Fintech, and Size-finder in apparel retail. With domain-specific AI, the time-to-value reduces significantly to the extent of 8-10 X compared to generic AI.
Intent accuracy is the ability of a chatbot to correctly predict the purpose of a user who is interacting with it. In percentage terms, intent accuracy is how many times intent was correctly detected out of 100 messages.
AI accuracy, on the other hand, is the ability to provide the right response or perform the desired action on behalf of the user. AI accuracy is a more robust metric because it considers not just the intent but also the ability to handle context switches and respond accurately, making it a harder metric.