Building PoC acceleration and realizing optimal MLOps services for our customers in collaboration with DataEgg.

1. Provision of cost-effective DX and AI development services through collaboration with DataEgg Inc.

Our Human Science has strengthened its partnership with DataEgg Inc. (Headquarters: Shibuya, Tokyo, CEO: Daiki Netsukata).

 

●DataEgg Inc.: https://dataegg.co.jp/

 

Recently, the expansion of DX (Digital Transformation) has been progressing rapidly, and in order to enhance corporate value and create new value, it has become an urgent issue for all companies to utilize the data accumulated so far and address the visible labor shortages. Many companies are also advancing the introduction and development of AI to address these challenges, but it is necessary to implement or develop AI with a sense of speed and further refine it into AI that can be used in practice. This time, through the strengthening of our partnership with DataEgg, we have made it possible to solve these challenges and optimize and streamline the series of AI development, operation, and maintenance processes represented by MLOps between the two companies, thereby increasing development speed and providing our customers with cost-effective and high-value-added services.

2. Customer Benefits from Strengthening Partnership with DataEgg

2-1. Accelerating PoC Development through Strengthening Partnerships

Many AI development vendors separate the development of AI models and the creation of training data, outsourcing the annotation work required for training data creation to annotation vendors. In particular, creating training data not only requires a significant amount of labor but also, if there is a lack of communication and understanding between AI development vendors and annotation vendors, it can lead to a decline in the quality of training data, a decrease in AI accuracy caused by that, and the need to redo the creation of training data, which often results in prolonged development periods. To respond to environmental changes and the flow of the times, and to enhance corporate value, it is necessary to advance DX with a sense of speed, especially by conducting PoC (proof of concept) in AI development in a rapid cycle, determining the direction of the developed AI, and shaping it into AI that can be used in practice.

 

Through the collaboration and enhancement of DataEgg's shortest one-month PoC service "Bakusoku PoC" and our annotation services, both companies can optimize the process and provide a service that accelerates the PoC phase from the creation of training data to the implementation and accuracy verification of AI, all while keeping costs down.

 

●DataEgg Services Offered: Bakusoku PoC

2-2. Providing optimal solutions that are close to the customer through collaboration with customer-centric companies.

Needless to say, each customer has unique challenges in the utilization of DX and data. When promoting DX and data utilization, it is important to start by considering whether AI is optimal and whether it is feasible with AI, rather than assuming AI is the solution. DataEgg and our company have provided flexible services for data utilization and DX, not limited to AI, while closely supporting our customers in addressing these challenges, and have received high evaluations.

 

In order to continuously use AI as a practical tool, maintaining accuracy and responding to the ever-changing needs of users requires not just development, but also an optimal maintenance plan that includes support and operations, as well as improvements such as tuning and additional learning tailored to the evolving input data. During this phase, it is crucial to provide solutions that align with our customers' challenges. The AI maintenance and operation service "Yuricago.AI" offered by DataEgg, along with the optimization of our additional learning annotation services, strengthens our mutual corporate policy of prioritizing customer support through partnership. This enables us to provide optimal services that cater to our customers throughout all processes of MLOps, from PoC to maintenance and operations.

 

●DataEgg Services Offered: Yuricago.AI

Our related blog: What is unstructured data? Explanation of how to utilize unstructured data

2-3. Strengthening through Partnerships and Providing High-Quality Services through Synergies in Areas of Expertise

The development of AI requires, in large part, ① the creation and construction of learning models and evaluation, and ② the creation of training data. However, in order to lead AI development to success, it is necessary to have knowledge and know-how in each area. Moreover, the more specialized the field, the stronger this tendency becomes.

 

DataEgg and our company have a proven track record in various fields, particularly in high-difficulty areas such as medical and text-related fields. By leveraging each other's knowledge and expertise, we contribute to the successful development and operation of AI across a wide range of fields, focusing on technically challenging AI development.

3. Development Achievements and Examples of DataEgg Inc.

Below is an example of DataEgg's development achievements to date.

Actual Case

Predictive Analytics and Optimization:

Building delivery demand forecasts and dynamic pricing strategies, predictive analysis, and optimization, etc.

 

PoC

Image Processing:

Receipt judgment OCR, age and gender estimation of faces, etc.

 

Natural Language Processing and Sentiment Analysis:

Call center emotion analysis of voice data and text data analysis, identification of customer emotions and intentions, etc.

4. Features of Human Science Annotation Services

Case Examples

AI Annotation Case Studies | Human Science Co., Ltd.

Case Studies of Sumitomo Heavy Industries, Ltd.

Case Studies of SCSK Corporation

A rich track record of creating 48 million pieces of training data

At Human Science, we participate in AI model development projects across various industries, including natural language processing, medical support, automotive, IT, manufacturing, and construction. To date, we have provided over 48 million high-quality training data through direct transactions with many companies, including GAFAM. We handle a wide range of annotation and data labeling, from small-scale projects to long-term large projects with 150 annotators, regardless of the industry.

Resource management without using crowdsourcing

At Human Science, we do not use crowdsourcing; instead, we advance projects with personnel directly contracted by our company. We form teams that can deliver maximum performance based on a solid understanding of each member's practical experience and their evaluations from previous projects.

Support for various data according to your needs

We handle a variety of input and output data, from labeling attributes of large amounts of unorganized and uncategorized data such as videos and compiling them into Excel or CSV, to adding label information to images and text data and describing them. 

Equipped with a security room in-house

At Human Science, we have a security room that meets ISMS standards within our Shinjuku office. This allows us to handle even highly confidential projects on-site while ensuring security. We consider the protection of confidentiality to be extremely important for all projects. Our staff undergoes continuous security training, and we exercise the utmost caution in handling information and data, even for remote projects.