“Artificial Intelligence Search, Deep Learning and Machine Comprehension”

AI deep tech startup that develops a Deep Semantic TA and QA Platform that understands the true intention of a user’s question to provide a single answer from a large unstructured data set.


  • Type of Business: IT Service, AI
  • Representative: Donghwan Kim
  • Homepage: www.42maru.ai
  • Corporate Address: Sinbanporo 310, 1F-7F, Seocho-gu, Seoul, Republic of Korea, 06533
  • Contact: sales@42maru.ai

The core of our technology is based on Question Answering. There are many ways machine understanding of data can help companies. From the rise of semantic search that powers smart devices to semantic search technology for the enterprise.

Key Features


Question and Answering (QA) uses a combination of language manipulation and search techniques to find the exact information you’re looking for and offer a direct answer to questions posed in a natural language. It is based on a closed Domain (topic-specific) questions.


Information Retrieval allows for data, in various forms, to be organised for easy access and indexed for quick retrieval. Search decides what content, and in what form you see whenever you enter a query.


Deep Learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data to perform complex tasks based on patterns.


Semantic Search attempts to interpret the user’s intent in a context, instead of keyword matching alone, by understanding entities and relationships within the content. Topics and concepts are linked and related information can be suggested.


Machine Reading Comprehension is the ability for computers to read and understand the unstructured text and then answer questions about it without the need to build an ontology set or any data formating.


Natural Language Understanding tries to deduce what questions mean, regardless of the way they are expressed, allowing users to interact with the computer using natural sentences. NLU provides optimal answers to user questions by utilizing various NLP technologies (POS, NER, Domain Classification, Intent Analysis, etc.) and deep learning technologies that perform Context Management to exchange context-based conversations and offer answers based on user-specific sessions and history.