Allganize, a startup that provides deep-learning based Natural-Language Understanding and conversational ArtificiaI Intelligence (AI) for enterprises, received $3.4 million Series A investment from SparkLabs Ventures and others on April 29. The Silicon Valley-based startup with Korean founder Changsu Lee also got backing from other investors for this funding round, like Seoul-based venture capital firms Fast Investment and Laguna Investment, Canadian VC Base Investment and existing investor Global Brain.

Helping enterprises organize using AI

Allganize was founded in 2017 with a focus to provide solutions to help clients manage documents scattered across various platforms such as Google Drive, Confulence, Slack, Jira and Zendesk. The startup’s deep learning-based, high-performance NLU technology enables companies of all sizes to apply AI technology to develop their own AI systems and services.

The conversational AI and chatbot service Alli.ai offers highly personalized customer experiences by recognizing the complex named entities and user intents of text from the data collected and analyzed from customers’ chat and voice messages using their proprietary NLU technology. Allganize’s technology has been well received in the global market with it getting business from some top firms like KDDI, Persol and many more.

“Our journey for bringing the best-in-class Natural Language Understanding AI to enterprises has just started in US, Japan, and South Korea,” Changsu Lee, CEO, Allganize

Funds to help push growth

The startup was founded by Changsu Lee, a Korean origin entrepreneur who had earlier ran another startup 5Rocks, that was dedicated to business intelligence and data analysis for mobile game developers and was acquired by Silicon Valley-based mobile advertising platform company Tapjoy in 2014.

With the latest round of funding, the company wants to accelerate its growth and take on exciting challenges. The startup wants to continue to push for the best practices of utilizing supervised learning, and distant supervised learning as a well-defined business process, using AI with minimal maintenance.

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