Achieving Faster PoC and Optimal MLOps Services for Customers through Collaboration with DataEgg

1. Providing cost-effective DX and AI development services through collaboration with DataEgg Co., Ltd.

Our company, Human Science Co., Ltd., has strengthened its partnership with DataEgg Co., Ltd. (Headquarters: Shibuya-ku, Tokyo, Representative Director: Daiki Netsukata).

 

●DataEgg Co., Ltd.: https://dataegg.co.jp/

 

Recently, the spread of DX has been rapidly advancing, but in order to increase corporate value and create new value, it is urgent for all companies to promote the utilization of accumulated data and respond to issues such as labor shortages that are becoming apparent. In order to address these issues, the introduction and development of AI is also progressing in many companies, but in order to do so, it is necessary to introduce or develop AI with a sense of urgency and tailor it to be usable in practical work. Through the strengthening of our partnership with DataEgg, we are now able to solve these issues and optimize and streamline the entire AI development, operation, and maintenance process, represented by MLOps, between the two companies. This will increase development speed and enable us to provide high-cost performance and high-value-added services to our customers.

2. Benefits for Customers through Strengthening Partnership with DataEgg

2-1. Speeding up PoC development through partnership strengthening

Many AI development vendors outsource the creation of AI models and the creation of training data to annotation vendors. In particular, creating training data requires a significant amount of work, and if there is a lack of communication and understanding between the AI development vendor and the annotation vendor, it can lead to a decrease in the quality of the training data, a decrease in the accuracy of the AI, and the need to redo the creation of training data, resulting in longer development periods. In order to respond to changes in the environment and the flow of the times, and to improve corporate value, it is necessary to proceed with DX with a sense of speed, and to conduct PoC (proof of concept) in AI development at a fast cycle, and to determine the direction of development AI and tailor it to be used in practical work.

 

By collaborating and strengthening the integration between DataEgg's "Bakusoku PoC" service, which can be provided in as little as one month, and our data annotation service, we are able to optimize processes and provide a service that speeds up the PoC phase from creating training data to introducing and verifying the accuracy of AI while keeping costs down.

 

●DataEgg Services: Bakusoku PoC

2-2. Provide the best solution that caters to customers by collaborating with customer-oriented companies.

Of course, in terms of DX and data utilization, each customer has their own unique challenges. When promoting DX and data utilization, it is important to not just focus on AI implementation, but also consider whether AI is the optimal solution and if it is feasible to achieve with AI. DataEgg and our company have received high praise for providing flexible services for data utilization and DX, while accompanying and supporting our customers with their specific challenges, rather than solely focusing on AI.

 

In order to continuously use AI in practical work as an AI that maintains accuracy and responds to constantly changing user needs, it is necessary to continuously improve through tuning and additional learning according to the changing input data, as well as maintenance and operation, from an optimal maintenance plan that does not end with development. In this phase, it is important to provide solutions that meet the customer's challenges, but the partnership between our companies is further strengthened by our shared policy of "putting the customer first", and with DataEgg's AI maintenance and operation service "Yurikago.AI" and our optimized additional learning annotation service, we are able to provide the customer with the best service that meets their needs throughout the entire MLOps process, from PoC to maintenance and operation.

 

●DataEgg Services: Yurikago.AI

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2-3. Strengthening of strengths through partnerships and high-quality service provision through synergy in areas of expertise

AI development requires two main steps: ① creating and constructing learning models, evaluating them, and ② creating teacher data. In order to successfully lead AI development, it is necessary to have knowledge and expertise in each of these areas. Furthermore, the more specialized the field, the stronger this trend becomes.

 

DataEgg and our company have a proven track record of handling various fields, particularly in challenging areas such as medical and text-related fields. By leveraging our expertise and knowledge, we will contribute to the success of AI development and operation in a wide range of fields, with a focus on high-tech AI development.

3. Development Results and Examples of DataEgg Co., Ltd.

Here are some examples of DataEgg's development achievements so far.

Actual Projects

Predictive Analytics and Optimization:

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

 

PoC

Image Processing:

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

 

Natural Language Processing and Sentiment Analysis:

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

4. Features of Human Science's Data Annotation Service

Achievements and Examples

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

Sumitomo Heavy Industries, Ltd. Case Study Introduction

SCSK Co., Ltd. Case Study Introduction

Rich track record of creating 48 million pieces of teacher data

At Human Science, we are involved in AI model development projects in various industries such as natural language processing, medical support, automotive, IT, manufacturing, and construction. Through direct transactions with many companies including GAFAM, we have provided over 48 million high-quality training data. We handle various annotations and data labeling, from small-scale projects to large-scale projects with 150 data annotators, regardless of industry.

Resource Management without Using Crowdsourcing

At Human Science, we do not use crowdsourcing and instead directly contract with workers to manage projects. We carefully assess each member's practical experience and evaluations from previous projects to form a team that can perform to the best of their abilities.

Corresponds to various data according to your request

We will label attributes to a large amount of data such as unsorted and uncategorized videos and compile them into Excel or CSV. We also provide labeling and description of label information for various input and output data, from images to text information. 

Equipped with a security room within the company

At Human Science, we have a security room that meets the ISMS standards in our Shinjuku office. This allows us to provide on-site support for highly confidential projects and ensure security. We consider confidentiality to be extremely important for all projects at our company. We continuously provide security education to our staff and pay close attention to the handling of information and data, even for remote projects.