Datasaur Raises Initial Funding of 60 Billion Rupiah
This funding round was led by Initialized Capital with the participation of HNVR, Gold House Ventures, TenOneTen and previous investors
Data labeling platform development startup Datasaur announced new seed funding of $4 million or over IDR 60 billion. This round was led by Initialized Capital, with participation from HNVR, Gold House Ventures, TenOneTen, and past investors.
Previously, this platform also had time to earn investation worth $ 3,9 million or the equivalent of IDR 58 billion after participating demo day in the Y Combinator accelerator program in March 2020. To date, the total funding that has been obtained has reached $7,9 million or more than IDR 118 billion.
The fresh funds raised will be focused on developing better NLP data labeling and modeling process efficiency for data scientists.
Although based in the United States, Datasaur was founded by an Indonesian entrepreneur, Ivan Lee. Companies develop intelligent tools to help data labelers work more productively and efficiently. This includes improving data privacy and security – often data labeling work is done privately outsourced.
As is known, the data labeling process is an important aspect in developing AI-based services, especially in model-based natural language processing (NLP). Datasaur handles all NLP models, including some of them entity recognition, document labeling, to parsing dependencies.
As the NLP industry continues to grow, many companies are interested in training models based on their own data sets. That way, companies can train models to handle some very specific tasks in a more efficient way.
Reporting from TechCrunch, Datasaur Founder & CEO Ivan Lee revealed that one of his goals since the beginning of developing this platform was to democratize AI, especially regarding nnatural language processing, and these new modeling features will make AI more affordable for many enterprises, even those without specific specifications.
Datasaur creates features that allow teams without data scientist, without engineer, to mark and label this data as desired, and it will also automatically train the model. This feature will be unlocked soon, so construction companies, law firms, marketing companies, who may not have a data engineering background, can still build NLP models [based on their training data].
Ivan also emphasized that he has a philosophy that is always focused on profitability, growing in a measurable way, not just growing by all means. He admits that he really considers every recruitment and its impact on business.
Currently, his engineering team is mostly based in Indonesia, and in terms of recruitment process, he is assertive enough to operate the company in an efficient way. According to him, by having a workforce that crosses geography and culture, employees can learn from one another, and that brings diversity to the company.
In March 2022, portfolio company GDP Ventures announced its acquisition of AI Convergent, technology development startup optical character recognition (OCR). Through this acquisition, both Datasaur and Convergent AI will integrate and expand their capabilities in the realm of OCR and data labeling.
Development of AI-based solutions in Indonesia
Indonesia is showing significant interest and growth in the development of AI-based solutions across various industries. Until now, there have been several companies that have seen the potential of AI and are trying to capitalize on it in this market.
One of them is Kata.ai, a technology company that focuses on developing artificial intelligence-based natural language processing in the form of chatbot has experience in assisting more than 150 businesses through technology chatbot.
Technology chatbot is a technological innovation that is able to walk side by side with humans. sophistication chatbot itself provides an opportunity for humans to focus on problems that cannot be handled by chatbot so that the preparation of the right operational strategy can be oriented towards a more efficient and productive business.
In addition, AI solutions have also penetrated developing sectors in Indonesia. In the HR sector, one of the developers of the Human Resources Intelligence System (HRIS), Catapa, recently launched a new feature HelpGPT, a chatGPT-based application that provides information on payroll taxes and labor regulations in Indonesian.
In other sectors such as agriculture, there are already attempts to use AI to optimize farming practices, crop monitoring and yield prediction. AI-based solutions can help farmers make data-driven decisions, leading to increased productivity and sustainability.
Within the healthcare industry, many related institutions are also exploring the use of AI for disease diagnosis, medical image analysis, and personalized treatment planning. AI-powered tools are being developed to help healthcare professionals provide better patient care.
Likewise in sectors that are growing rapidly in Indonesia, such as fintech, AI utilization opportunities continue to be explored. The financial industry is embracing AI to improve customer experience, optimize risk management and fight fraud. chatbot AI-powered and virtual assistants are becoming more prevalent in customer service.
Regarding the development of AI-based solutions, the Indonesian government also actively supports AI research and development through various initiatives and policies. They realized the potential of AI in driving economic growth and improving public services.