Crowdsourcing methods involving end users are likely to result in poor quality data even for large amounts.
Poor quality makes it impossible to commercialize and inevitably results in junk data.
We prioritize quality over quantity. Using the knowledge and experience obtained from seven years of commercializing AI services and labeling data
Bach AI DATA wants to provide high-quality data for product development and commercialization.
Once a topic is selected for commercialization, our AI engine and professional editors generate data that fits that topic according to our own methodologies.
Our Machine Learning technology allows AI to present multiple outputs on a particular topic and allows professionals to learn and select the most appropriate ones.
The AI learning process is followed by cross-validation with professionals using objectified indicators and self-developed inspection systems, extensively inspecting and modifying them.
Instead of a typical dataset that supports one output per input, BACH supports multiple outputs per input, allowing the learning data to be scaled radially.
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※ These figures are updated every 15th and 30th of every month.
BACH focuses on commercialization and pursues concessions to present its own high-quality AI solution, as well as a corpus collection and processing system for language education.
A comparison of the conversation dataset to a table shows the difference in data volume, quality, and scalability. The conversation dataset processing has unmatched scalability.
The following graph provides a comparison of foreign companies.
It shows that our engine's performance is a world-class level.
Personalized AI solutions tailored to the needs of your customers through consulting.
For language education, the solutions are presented as follows:
Assessing students' skills using internationally recognized evaluation indicators.
e.g. TOEFL Juinor, Lexile Level, CEFR, etc.
Analyze the proper data according to each student's level.
Data-driven analysis of curriculum, textbooks, and teaching methods is conducted by converting them into data.
Provide a corpus of data tailored to the needs of each clients.
Providing a continuous, on-off-line experience.
Conversation practices can be conducted anywhere, anytime.
Bach provides real-time recommendations for answers.
Anyone can practice English conversation in a variety of ways.
This is an example use cases in an actual application based on above examples.
We can offer a conversation corpus where you can freely discuss a specific topic.
As well as the text labeling (conversation set processing) described above, various data labeling is possible, such as image and image labeling as well as voice labeling.
The data processed by our engine can be commercialized in various fields as follows.
Several organizations have requested our AI solutions, and we are currently attracting partners by extending core areas such as Visual Question Answering (VQA)
and Question Answering with Image Scene Graphs (GQA) as well as corpus data.
Through AI consulting, we provide data quickly and easily with a systematic processing and inspection system.
The AI platform data labeling service, conducted with language professional editors, enables accurately labeled data collections to be used in machine learning models.
Our AI inspection engine and dual total inspection system boast high accuracy and data quality.
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