By Industry

By Technology



Overview and why we
need service

The graphical description of information and data is known as data visualization. Data visualization tools, which include visual components like as charts, graphs, and maps, make it easy to view and comprehend trends, outliers, and patterns in data.

Predictive Analysis Service benefits

Analysis Service

We are a small, but growing team. Our
expertise includes growth marketing, design,
software development, and product management.



Data science and data engineering jobs should be automated. Train, test, and deploy models across various corporate applications in real-time. Extend shared data science capabilities to hybrid and multi-cloud systems.



Our team can create Speed Harness pre-built apps and models. You can assist data scientists and business teams communicate and model build faster by using our cutting-edge and open source technologies.



To handle the complete data science lifecycle, use a centralized platform. Processes for development and deployment should be standardized. Develop a unified framework for data governance and security throughout the enterprise.

Which industries can benefit from our services


Medical Care

Medical institutions are always challenged to keep operational expenses under control while improving patient outcomes. Predictive analytics can help clinicians make precise diagnoses or predict the likely outcomes of therapies for patients with certain diseases.



Retailers utilize artificial intelligence for predictive analytics to provide custom-tailored items and individualized customer care." It also allows merchants to optimize their labor. It also aids in the mapping of a customer's journey and provides merchants with vital information on how prospects and leads progress through the marketing and sales funnel to become customers.



People rely on banks to seek loans, manage their money, and prepare for the future. Banking industry companies are increasingly depending on predictive analytics to improve customer service, increase efficiency, and identify flaws that might lead to major difficulties later.



professionals in the electromechanical engineering business frequently utilize reliability predictions to quantify the likelihood of system failure, taking into account stress factors, operational conditions, and quality standards.



Predictive analytics, on the other hand, has revolutionized the game by implementing robust, preventive procedures that identify and analyze risks before they penetrate systems more effectively than people can.



We provide the application platform, a comprehensive end-to-end platform for creating corporate AI apps that enable enterprises to harness the potential of AI-enabled predictive analytics for nearly any use case

Our Application Platform includes a comprehensive set of tools and capabilities for designing, creating, deploying, and running corporate AI applications on a large scale. Organizations may use this Application Platform to 25-fold speed up the creation of enterprise AI apps on cloud platforms such as AWS and Azure, and deploy them in one-tenth the time of conventional ways.

We also provide a portfolio of prebuilt, SaaS enterprise AI solutions that use predictive analytics for a growing variety of use cases such as predictive maintenance, inventory optimization, fraud detection, and anti-money laundering.




Data science

Our Studio assists in the operationalization of AI by offering tools for preparing data and building simulations anywhere using open source code or visual modeling.


Decision optimization

Our Decision Optimization improves outcomes by combining prescriptive analytics with predictive insights from machine learning models.


Visual modeling tool

With comprehensive algorithms and models that are ready for use, our Modeler solution can help you access data assets and current applications.


Statistical analysis software

Ad hoc analysis, hypothesis testing, geographical analysis, and predictive analytics are used in our Statistics to address commercial and research challenges.

case studies

Financial service companies who are unable to develop in response to technological advancements will fail. Technologies like AI not only improve services but also improve the consumer experience.

Tech stack used for solutions

Machine Learning
Artificial Intelligence
Deep Learning
Data Mining

Frequently Asked Questions

Predictive analytics refers to a set of statistical approaches derived from data mining, predictive modeling, and machine learning that evaluate current and historical data to forecast future or otherwise unknown occurrences.

Making use of statistics, computer science, and data. Statistical models search for trends in historical data. They compute the probability for future events in this manner. For this aim, specialists typically employ machine learning methods (a subject of artificial intelligence and computer science).

Enterprise AI relies heavily on predictive analytics. Enterprise AI systems operate as "prediction engines," giving insights to drive actions that improve company operations and performance.

When combined with artificial intelligence (AI), the insights gained from these sophisticated systems will be the key to future more accurate and timely forecasting. Predictive analytics uses machine learning and historical data to enhance operations such as weather patterns, customer behavior, and gas price swings.

Predictive analytics allows your company to optimize operations by forecasting the most likely outcomes. These predictions directly guide the action to be taken with each scenario or use case, such as marketing to people who are most likely to buy and identifying those who are most likely to conduct fraud.

Data modeling, machine learning, AI, deep learning algorithms, and data mining are technologies of predictive analytics statistical approaches. The unknown event of interest is frequently in the future, although predictive analytics may be used for any form of the unknown, whether in the past, present, or future.

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