CIO Bulletin

Allganize – Helping Enterprise Customers Automate Answering Questions from a Myriad of Complex Text Documents

If you have noticed an increase in chatbot use, you are not alone. More and more enterprise organizations are using them to automate aspects of the customer experience. With less reliance on service agents and live agents, organizations are realizing significant cost savings and are becoming more efficient. A chatbot system uses conversational artificial intelligence (AI) technology to simulate a discussion (or a chat) with a user in natural language via messaging applications, websites, mobile apps or the telephone. It uses rule-based language applications to perform live chat functions in response to real-time user interactions. A chatbot is often described as one of the most advanced and promising expressions of interaction between humans and machines. These digital assistants streamline interactions between people and services, enhancing customer experience. At the same time, they offer companies new opportunities to streamline the customer’s engagement process for efficiency that can reduce traditional support costs.

Allganize is one such company that helps insurance, finance, and SaaS companies automate answering questions from a myriad of complex text documents. Its applications include assisting service representatives in customer support centers, enhancing the search experience on the website and mobile app for end users, providing customer support chatbot and extracting important entities from text contracts for underwriters and agents. Unlike its competitors in the enterprise AI space, Allganize’s proprietary technology does not require any manual data tagging, making it very quick to implement while providing best-in-class results accuracy. By adopting Allganize, it is proven that an agent can handle 3X - 5X more tickets per day as the AI is capable of answering 50% - 80% of questions automatically.

AI-Based Chatbot Products Leveraged

Alli AI: It is an Industry-Leading AI Answer Bot intelligently responds to customers through natural chat conversation flows, enabling the automation of up to 80% of support tickets. This allows customers to get serviced faster while improving employee productivity. Alli AI Answer Bot accurately responds to internal staff inquiries about human resources, accounting, information systems, sales support and other general questions. This decreases unnecessary support exchanges and reduces the amount of human labor required to address them. Best of all, Alli Answer Bot automatically responds to chat support inquiries from customers that visit your websites. By reducing the number of phone and e-mail inquiries requiring human attention, this leaves your support agents to handle larger support requests while improving customer satisfaction. Alli Answer Bot can personalize the chatflow based on the context of the conversation. Enabling AI automation of complex tasks, Alli understands the nature of inquiries and provides the right solution, such as responding to the inquiry with the right form.

Cognitive Search AI: Finding the right answers quickly can be difficult when a company has hundreds of documents to sort through. Allganize has perfected a smart search solution that instantaneously provides the relevant answer to a search inquiry, giving employees back that valuable time to their workday. Cognitive Search will automatically extract relevant information to deliver accurate results. With support for multiple file types, including unstructured documents, the intelligent search extracts answers quick, allowing agents to handle up to five times more support tickets. Their AI solution understands the search query using natural language understanding and will provide the answer in sentence or paragraph form, making contact center service representatives' experts in their field.

NER API: It extracts meaningful keywords from any text descriptions and automatically tags them with specific labels. Eliminating the need for manual tagging, this automates document processing. NER Analyzer uses machine learning to automatically classify keywords and reveal the meaning of the text. It extracts meaningful information about people, places, and events in order to better understand customer tone along with conversational flows. Review Analyzer identifies recurring themes and topics within comments and reviews. Without having to read every single review, this allows retailers to quickly and automatically gain insights on product feedback. Typically, it will take an employee an entire day to manually tag 500 phrases to track data for text classification (named-entity). With Allganize's text classification API, you can convert that manual data work to be 100% automated, saving employees significant time back towards their day and increasing employee efficiency.

Sentiment API: About 47% of consumers sort through reviews and look for sentiment (the tone in which a review is written) upon making a purchasing decision. The sentiment API can automatically parse and gauge the severity of your customers' feedback or support tickets based on positive, negative and neutral words used. Sentiment Analyzer uses machine learning to reveal insights on the meaning of written text. It automatically extracts information about people, places, and events in order to provide accurate customer sentiment feedback. The text classification is based on natural language understanding which automatically learns user intent in order to formulate responses to inquiries. This model can be trained further to customize user intent for your specific audience.

Changsu | Founder & CEO

He studied Computer Science at KAIST, and has worked as a back-end engineer for 15 years. He has had a successful exit with his previous startup called 5Rocks, a mobile app analytics company, and is currently based in Houston, TX.