Mukesh Infoserve’s IOT advisory approach, combined with digital and engineering experts, helps companies seamlessly bridge the physical and digital worlds to create connected solutions at scale.
The internet of things (IOT) is booming, with more than 20 billion connected devices expected worldwide by 2020.
Mukesh Infoserve’s expertise from device to cloud and enterprise applications to big data analytics enables us to architect and implement end-to-end secure commercial-ready IOT solutions at a larger scale. Our solutions integrate the best of Mukesh Infoserve and industry components to provide seamless actionable insights.


Accelerated AI data pipelines across edge, core and cloud Simplify, integrate, and accelerate your journey to AI.
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before.
Mukesh Infoserve has been at the forefront in implementing advanced machine learning driven solutions for different verticals and sectors that are playing a pivotal role in various aspects of the business process.
AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.

Mobility Solution

Mobility is entering mainstream information technology (IT) as enterprises look at mobility as a key enabler for their business process automation. Mobility solutions for media organizations improve external customer experience and internal employee/field force productivity.
With the rapid increase of smart phones and high speed network, there has been a drastic shift in customer and employee expectations. While consumers are increasingly using mobile applications to perform complex banking transactions, the workforce is looking to access enterprise applications and business data on the go. Companies need a well thought out strategy to meet these expectations at every stage of the digital journey.
Mukesh Infoserve developing native mobile applications for iOS, Android, Windows Phone and Windows 8, accelerating time to market for responsive, multi-device applications. This ready-to-use framework optimizes development costs by helping users build reliable, scalable, and maintainable applications that require minimum effort for adding or removing features.


Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, Analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.

Organizations may apply Analytics to business data to describe, predict, and improve business performance.

  • Predictive Analytics
  • Prescriptive Analytics
  • Enterprise Decision Management
  • Descriptive Analytics
  • Cognitive Analytics
  • Store Assortment and Stock-keeping Unit Optimization
  • Big Data Analytics
  • Retail Analytics
  • Supply chain Analytics
  • Web Analytics
  • Sales Force Sizing and Optimization
  • Price and Promotion Modeling
  • Predictive Science
  • Marketing Optimization and Marketing Mix Modeling

Since Analytics can require extensive computation, the algorithms and software used for Analytics harness the most current methods in computer science, statistics, and mathematics.

Big Data

Big data is a term used to refer to the study and applications of data sets that are too complex for traditional data-processing application software to adequately deal with. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source.
Big data was originally associated with three key concepts:

  • Volume
  • Variety, and
  • Velocity

Other concepts later attributed with big data are Veracity and Value.

The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable

  • Cost Reductions,
  • Time Reductions,
  • New product development and optimized offerings, and
  • Smart Decision Making.

When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:

1. Determining root causes of failures, issues and defects in near-real time.
2. Generating coupons at the point of sale based on the customer’s buying habits.
3. Recalculating entire risk portfolios in minutes.
4. Detecting fraudulent behavior before it affects your organization.

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