42Maru builds a Question Answering platform that finds a Single, Specific, Correct Answer based on Deep Learning
Business Model:
Revenue: $5M
Employees: 11-50
Address: .
City: Gwanak-gu
State: seoul teugbyeolsi
Zip: 08826
Country: KR
1) What we do • We develop a deep learning based QA(Question Answer) system that understands the true intention of the question and provide a Unique Correct Answer 2) Why • AI based Smart machines are penetrating into our everyday lives, there are signals of paradigm shift from the traditional web search system to QA system. 3) Market Size • Globally expecting a $50bn market size by year 2025 (+50% YoY). • 50% of all searches will be done by voice searches by year 2020. 4) Technology • We have core technologies in IR(Information Retrieval), Triple, MRC(Machine Reading Comprehension), Paraphrasing, NLU/NLP(Natural Language Understanding/Processing) etc. 5) Core Competency • Our system is different to the existing system because we have a high accuracy, self expansion of KB(knowledge base), low GPU cost, quick response. • This is the reason why we have the globally the first deep learning based QA commercial version in Korean. • We have experience in a commercial version of sematic search which has similar logics with QA system and also have multi-language web-search experience as well. • Strong team with CEO having +20yrs of related work experience. 6) Target Markets • Connected Cars, Smart Speakers, Home IoT, Home Robots, Smart Toys, Personal Assistants, Chatbot Apps, Intranet, KMS. 7) Business Model • Planning B2C penetration through B2B2C Alliance and set for global expansion with multi-language support. 8) References • B2B projects with some major TELCOs in Korea, such as LG and Korea Telecom, and also with big ship building industries and financial institutions. 9) Competitors • Competitors have QA systems based on either Rule-based or Inference based which has limitations on commercialization. 10) Team • CEO: Pioneer in the search engine industry with +20 years of experiences, deep learning expert • Total member of 27 (22 QA specialists) (hiring currently more)
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Announced Date | Company | Transaction | Money Raised |
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Announced Date | Transaction | Number of Investors | Money Raised | Lead Investors | 7/2018 | Pre Seed Round | 2 | - |
Techstars Techstars London Accelerator Techstars Techstars London Accelerator |
11/2019 | Pre Seed Round | 1 | $89k |
Samsung Electronics Samsung Electronics |
11/2017 | Pre Seed Round | 1 | $445k |
Korean Government TIPS Program Korean Government TIPS Program |
12/2017 | Debt Financing | $0 |
Dayli Partners Spring Camp Dayli Partners Spring Camp |
8/2020 | Debt Financing | 1 | $1.7M |
Korea Development Bank Korea Development Bank |
7/2018 | Pre Seed Round | 2 | - |
Techstars Techstars London Accelerator Techstars Techstars London Accelerator |
12/2017 | Debt Financing | 2 | $1.2M |
Dayli Partners Spring Camp Dayli Partners Spring Camp |
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