AIZOTH Inc. | AI System Development and Consulting in Tsukuba, Ibaraki, Japan | AIZOTH, Tsukuba City, Ibaraki Prefecture, Japan, provides the means to transform data into value through AI technologies such as Multi-Sigma, an AI analysis platform, under its vision to \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

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Multi-Sigma

Bringing the Power of AI to R&D

Start with minimal data and cost
No programming required AI analysis platform

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Trusted by the World’s Leading Companies

About Multi-Sigma

Multi-Sigma is a no-code AI analysis platform that allows you to perform predictions using deep learning and Bayesian analysis, and optimize multiple objective variables through genetic algorithms without the need for programming, directly from your browser. This platform supports the efficiency of R&D by optimizing various inputs such as material quantity, temperature, and time, and addressing multiple objectives such as quality, cost, and environmental impact using innovative experimental design methods.

Achievements

Cumulative Number of Users
Cumulative Number of Users
More than 300
Awards

Awards

4th TCI Venture Award

Excellence Award

35th Small and Medium Enterprise
Excellent New Technology and New Product Award

Excellence Award

3rd Ibaraki Innovation Award

Excellence Award

Ecotech Grand Prix 2021

Corporate Award

AI Summit London 2025

Finalist

qcp Startup Pitch 2025

HIGHRESO AWARD

           

Multi-Sigma 4 Key Points

1

High Accuracy Prediction with Minimal Data

By finely tuning deep learning, it is possible to achieve high-accuracy predictions without overfitting, even with minimal data.

2

Explainable AI

Through factor analysis, it is possible to quantitatively analyze the magnitude and direction of contributions of explanatory variables, making AI, which is often considered a black box, explainable.

3

Multi-objective Optimization

The AI automatically explores conditions that satisfy multiple objectives simultaneously. From the Pareto solution set, it extracts conditions that offer the optimal balance for the customer.

4

Reducing Costs for Safe Implementation and Maintenance Management

Built on the Google Cloud Platform, this data-secure SaaS application eliminates the need for customers to prepare hardware and software. You can perform AI analysis using your usual PC, laptop, or tablet from a web browser.

Solutions

Product Design

  • Optimization of design parameters
  • Robust Optimization
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Mechanical Engineering

  • Optimization of manufacturing conditions
  • Reduction of environmental load
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Material Development

  • Optimization of material properties and manufacturing conditions
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Smart Agriculture

  • Yield prediction
  • Optimization of production and processing processes
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Optimization of Medical Treatments

  • Risk assessment for severe cases
  • Proposals for optimal treatment policies tailored to patient conditions
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Marketing

  • Exploration of optimal product specifications for customer segments
  • Exploration of the most desirable customer attributes
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Introduction of Functions

Multi-input Multi-objective Analysis

General automated machine learning (AutoML) outputs only take one prediction function, but our application can predict up to 100 objective variables from up to 200 explanatory variables, and it can reverse-analyze the 200 explanatory variables to satisfy the conditions of 100 objective variables simultaneously. This is the world's only application that can do this as of March 2024.

Utilization of Deep Learning Techniques

You can use both data analysis through neural networks and Bayesian optimization, which are the two major techniques in deep learning. It allows for analysis combining a neural network that demonstrates power with relatively well-organized data (about 20 or more) and Bayesian optimization that shows strength in sequential optimization from a minimal amount of data (around 3 to 5).

Predictive AI × Optimization AI

It is possible to simultaneously execute prediction using deep learning and optimization using genetic algorithms in one application. The optimization AI can automatically explore multi-objective optimal solutions while using predictive AI.

Precise Optimization

Utilizing genetic algorithms, it is possible to perform multi-objective optimization. You can set the maximization, minimization, and target value conditions of objective variables as well as the constraint conditions of explanatory variables.

Factor Analysis

Using techniques such as predictive model generation and sensitivity analysis, it is possible to quantitatively evaluate the extent to which each explanatory variable contributes positively or negatively.

Auto-tuning of Hyperparameters

You can automatically tune hyperparameters (parameters that set the behavior of machine learning algorithms), which are considered essential skills for AI engineers. This allows for high-accuracy prediction while controlling overfitting with a single button press.

AI Experimental Design Method

By transitioning from traditional statistical-based experimental design methods to AI-based experimental design methods, you can solve complex interaction problems, improve predictive accuracy, and achieve multi-objective prediction and optimization. This simplifies experimental design and eliminates unnecessary efforts.

Integration of Various Data

You can handle diverse data, such as categorical variables and image data, using image analysis tools and parameter diversity handling tools. This allows for spectrum decomposition and the breakdown of explanatory variables to solve complex problems.

Advanced Data Preprocessing Tools

Along with various preprocessing tools to enhance predictive accuracy, it includes tools to enable high-accuracy prediction even for rare or biased data.

           

Customer Stories・Customer Interviews

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#Customer Stories
#Customer Interviews

Customer Interviews
Kagome Co.

Customer Interviews
SWCC Corporation

Multi-Sigma Blog

We publish articles with information about Multi-Sigma updates and tips on how to utilize it effectively.

Blog List

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