One stop solution for all your AI analytics need.


Mateverse understands that a trained Predictive Analytics model or a dashboard full of myriad KPI's is just the tip of the iceberg for all the hard work that goes behind it.

Along with multiple automated fetaures, the platform comes packed with a complete BI suite capability




Data Experts spend 80% of their time in Data Preprocessing. Mateverse sets aside this difficulty, from reducing the time spent to multiple times lesser, even when opting for customization along the way.

Visual Interface for Database Operation & SQL

  • Database Table Join
  • Data Select: Over 100 function for various types of Data Select
  • Create New Tables
  • Bulk Operations
  • Complex Grouping

Automatic Missing-Value Treatment(ML-based/patent pending)

  • It analyses the neighboring values and underlying pattern and various statistical distributions in the data to predict the missing values, which significantly improves the quality of the predictive model

Automatic Outlier Detection Both Supervised and Unsupervised (ML-Based)

  • The family of algorithms automatically identifies the latent and dominant distribution viz., Binomial, Bernoulli, Poisson and many more, even the ones which are starting to emerge in the dataset and then scores each sample/row on its susceptibility to being an outlier. useful in; Detecting Fraud in the financial transactions data before it becomes mammoth.

Finding the perfect fit for a model, requires a professional to run many iterations and narrow down to the most accurate, and least biased models. Mateverse handles the modelling part by running a proprietary Meta-Engine in the background, which tried to understand the data like a Data Scientist would approach it to hand out the best fits from them

Supports over 10+ ML libraries

  • Numpy, Pandas, Seaborn, SciKit-LEARN, SciPy, Tensorflow, Keras, Matlib Plot, ARIMA, XG-Boost, LightGBM.

Automated ML

  • Classification
  • Regression
  • Time-series Analytics (ARIMA, Prophet, XG-Boost, Holt-Winter, and LSTM Based Regression)

Feature Selection

  • Automated Feature Selection
  • Automated Hybrid Feature Synthesis
  • Assisted Feature Select in the Manual Mode

Numerous accuracy computation metrics

  • Accuracy of a model should not be taken at face-value. Run the model through Mateverse’s in-built and popular Accuracy Calculation Methods to ensure accuracy in any environment

Model Interpretation

  • White boxing the black box
  • Complex confusion metric
  • Multiple graphs to understand the training process
  • Hyper-parameters used

ML Ensembles

Ensemble Models combines several sub models into a single, most efficient predictive model. This technique of ensembling is used to:

  • Avoid biases in the training processes
  • Tackle biases and improve the end prediction


Real-Time Dashboards

Mateverse’s Real-Time Dashboard updates itself with current data, which leads to quicker decision making through data monitoring. They come in handy for:

  • Management
  • Logistics Management
  • Stock Markets
  • Credit Modelling
  • Sales Monitoring and Forecasting
  • Supply Chain Analytics

Visualization

Visualizations help put derived insights into comprehensible formats. Only then can it be read easily and achieve the desired impact. Mateverse has over 90 different types of graphs and other visuals for:

  • Numerical Data
  • Categorical Data
  • Time series
  • Geographical data
  • Pivot tables
  • Chord Diagrams

We understand that Data Science and Complex Business analytics are hard subjects and requires years of efforts and study, which sometimes can get overwhelming to even the most experienced ones.

DB and Data Table Operations

  • Database Table Join
  • Data Select: Over 100 function for various types of Data Select
  • Create New Tables
  • Bulk Operations
  • Complex Grouping

Versioning

  • To facilitate and promote constant experimentation in the team and to not disturb the work of others in the team, Data Analysts/ Data Scientist get to fork the dataset from any screen that they’re working on to a new version which is easily switchable and accessible to other team members.

Machine Learning

  • Complex Confusion Matrix
  • Feature Importance
  • Model optimization method
  • Feature Engineering

Advanced Business Rules Engine

  • Programmatic Analytics





Consumption.


Mateverse cuts down any effort towards converting the files while uploading the Excel files, as all common database formats are supported by Mateverse.



Real-time Dashboards

Mateverse’s Real-Time Dashboard updates itself with current data, which leads to quicker decision making through data monitoring. They come in handy for:

  • Inventory Management
  • Logistics Management
  • Stock Markets
  • Credit Modelling
  • Sales Monitoring and Forecasting
  • Supply Chain Analytics

Visualization

Visualizations help put derived insights into comprehensible formats. Only then can it be read easily and achieve the desired impact. Mateverse has over 50 different types of graphs and other visuals for:

  • Numerical Data
  • Categorical Data
  • Time series
  • Geographical data
  • Pivot tables
  • Chord Diagrams

Programmatic Analytics

Programmatic Analytics unleashes the full potential of Data Science performed at scale, where the market-wide Analytics can be productized to produce results and adapt to varying environments automatically. For the first time in the ML industry, decision makers can look at the metrics that matter, rather than watching hundreds of KPIs on the Dashboard which are all equally confusing. We have designed the infrastructure in a way that these models can work together as a single unit. Some of the use cases of Programmatic Analytics are:

  • Marketing analysis
  • Predicting Sales
  • Site Clicks
  • Demand

Model accessibility

  • Use APIs
  • On Platform
  • Download Weights




Data Preprocessing.


Data scientists/analysts spend numerous hours in the data cleaning process, and MateVerse is the only platform in the world to have automated the pre-processing phase with various proprietary technologies by bringing down the time taken by 80%.




  Automatic Missing-Value Treatment

Automated Unsupervised (ML-based/patent pending):

It analyses the neighboring values and underlying pattern and various distributions in the data to predict the missing values, which significantly improves the quality of the predictive model.


   Automatic Outlier Detection

Both Supervised and Unsupervised (ML-Based/Patent-pending):

The family of algorithms automatically identifies the latent and dominant distribution viz., Binomial, Bernoulli, Poisson and many more, even the ones which are starting to emerge in the dataset. It saves the dataset from being prone to the Biases that these outliers transmits to the predictive model. It also helps data scientists and analysts to perform preventive analytics like Detecting Fraud in the financial transactions data before it becomes mammoth.







Visual Interface for Database Operation & SQL.




Import data from multiple sources

We understand that in an organisation data can be in numerous formats and can be compiled under MateVerse while supporting over 10+ databases in formats such as CSV, Excel,Multiple DB support such as MySQL, postgres, Mssql etc. Supports any big data lake


Data table Join

To use different sources of information in the modelling data need to be compiled and can be a time-intensive task. With mateverse, it can be used as a drag and drop solution.


Data Cleaning

A data scientist/analyst spends innumerous amounts of time in cleaning their data sometimes even taking weeks and months of their time. MateVerse has wholly automated the data cleaning process with features that can be used as a click and go solution, Outlier detection, Missing value imputation, Data formatting, And much more...


Complex Grouping

At times, the same dataset requires to extract some particular features and might need to apply some complex functions such as group by operations etc. Using MateVerse, this can be used a click and go solution.







Machine Learning.


With the technological prowess of ML, Mateverse has been trained in over 100,000+ datasets to aid in multiple segments of the data journey with automated feature selection, numerous optimization methods, explainable ai, ml ensembles and much more.



Auto ML.



Classification analysis draws conclusions from the input preferences given for training the class labels/categories for the new data and can be used to identify defects in products, predict loan defaulters, dip in demand.


Regression analysis is useful when continuous data is available and can sort out which variables have the most impact. Businesses can use regression analysis to explain a phenomenon, predict things or make impactful decisions. Some of its use cases are determining price based on location and demand forecasting.


Time series analysis involves developing models captured from historical data collected in constant time intervals and analysis performed can determine long term trends or forecast. Time series is widely used for non-stationary, time-specific data to optimising sales, understanding demand, trends etc.







   Feature Selection

Automated Feature Selection:
Determine which variables/features to select and keep, and diligently eliminate those that create noise. Mateverse assists a Data Analyst/Scientist in selecting the variables that speeds up training, easily understandable and most accurate models

Assisted Feature Select in the Manual Mode:
The platform pulls the right graphs like Chi-Square Test, Correlation Analysis through the Pearson Coefficient function, LDA, PCA, Anderson Darling Test.

Users can also choose the model optimization method as well as the loss calculation method, for your specific need and the quota to allocate for the test and validation test can also be decided.

   Multiple Optimization Methods

Calculation Methods - inbuilt:
Evaluate a model based on a number of metrics. Choice of metrics influences how well the model will work in the future. The accuracy of a model should not be taken at face value. Run the model through Mateverse’s in-built and popular Accuracy Calculation Methods to ensure accuracy in any environment.


   Explainable AI

Understanding why a Machine Learning model makes a certain prediction is crucially important, as it can avoid mistakes that machines may make and therefore guide it to make the right decisions.

  • White boxing the black box
  • Complex confusion metric
  • Multiple graphs to understand the training process
  • Hyper-parameter used

   ML Ensembles

Ensemble Models combines several submodels into a single, most efficient predictive model. This technique of ensembling is used to:

  • Avoid biases in the training processes
  • Tackle biases and improve the end prediction






Supports over 10+ ML libraries.







Access Management Control.


The AMC allows the admin to direct tasks assigned to the data scientists/ analysts and have them work on multiple databases simultaneously.



   Designed and Built for Teams

For Teams of Analysts or Data Scientists, Mateverse is fully equipped with a system that assigns each Data Science individual jobs, and upto 20 people can SIMULTANEOUSLY, work on the same dataset.

  • Supports upto 20 users
  • Simultaneous Accessibility

   Access Management System

  • Admin/Project Lead can select and control the access to the platform for the other team members consisting of Data Analysts and Data Scientists
  • Reviewer Page It gives a 360-degree view of all the activities that the data scientists and analysts are performing on the dataset even at the most granular level like what functions/transformations have been applied to each and every column arranged in chronological order across multiple versions of the same data set