The transition to digital data and faster document processing remains a significant challenge for many businesses. Despite advances in technology, much of the work still relies heavily on paper or static PDF files, from obtaining signatures to managing complex loan applications. This reliance on traditional methods leads to time-consuming, labor-intensive processes, especially in highly regulated industries like healthcare, banking, legal, and supply chain management. As companies struggle with the heavy burden of document management and compliance, the advent of AI-based document processing offers a groundbreaking solution. By harnessing deep learning technologies, businesses can now automate document workflows, drastically reducing manual efforts, boosting efficiency, and enabling the handling of larger volumes of documents without escalating operational costs.

At the forefront of this digital transformation is Allganize, a company specializing in AI-driven solutions tailored for insurance, finance, and SaaS enterprises. Allganize’s innovative technology automates the analysis of complex text documents, speeding up responses to customer inquiries, enhancing search functionalities on websites and mobile apps, and efficiently extracting essential information from contracts. What sets Allganize apart is its proprietary AI, which eliminates the need for manual data tagging, allowing for rapid implementation and delivering superior accuracy. The impact is profound: companies that adopt Allganize experience agents managing 3X to 5X more tickets daily, with AI autonomously handling 50% to 80% of queries.

This advancement represents a pivotal shift in document processing, where AI not only streamlines operations but also empowers businesses to scale efficiently while maintaining high levels of accuracy and compliance.

Simplifying Document and Automation Process

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 Lee | Co-Founder & CEO

Changsu Lee graduated with a bachelor's degree and master's degree in computer engineering at KAIST. After going through companies such as SKT and GameOn, he started 5Rocks, a mobile game data analysis startup, and then sold it to Tapjoy. He is currently based in Houston, TX.

“We are not just automating tasks; we are redefining how businesses manage and process their most critical documents, enabling them to achieve more with less.”