Digital IX

Artificial Intelligence

Statistical Analysis

Statistical analysis involves collecting and scrutinizing every data sample in a set of items from which samples can be drawn. A sample, in statistics, is a representative selection drawn from a total population. The goal of statistical analysis is to identify trends, relationship or a pattern.

  • Exploratory Data Analysis: Describe the nature of the data to be analyzed and explore the relations between data elements. EDA also helps understand and quantify features of the population.
  • Hypothesis Testing: The purpose is to design experiments, measure the results and draw the conclusions on the Population based on the samples. This helps create a model to summarize the understanding of how the data relates to the underlying population and prove (or disprove) the validity of the model.
  • Bayesian Methods: This is a method of inference in which Bayes’ theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It has a wide range of applications including science, engineering, philosophy, medicine, sport, and business

Machine Learning (ML)

The goal of machine learning is to develop methods that can automatically detect patterns in data, and then to use the uncovered patterns to predict the outcomes of interest.

  • Supervised Learning: This is a process where the algorithm learns from the past observations and creates a prediction model. This model is utilized to predict the outcome of a given set of input conditions.
  • Unsupervised learning: The goal for unsupervised learning is to model the underlying structure or distribution in the data in order to learn more about the data. Algorithms are left to their own to discover and present the interesting structure in the data.
  • Recommender Systems: These systems filter the choices for a user/product and personalize the recommendations based on the user’s preferences/propensity.

Natural Language Processing (NLP)

NLP refers to a method of communicating with an intelligent system using a human language. It involves making computers to perform useful tasks by automatically interpreting and making decisions using both speech and Text

  • Topic Mining: Identifying the key topics in a corpus of text is called topics. These techniques are used to identify trends, user preferences and new ideas that were discussed in increasingly proliferating information generation.
  • Entity Extraction: This seeks to identify pre-defined categories from a corpus of text such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
  • Sentiment Analysis: This is to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to the voice of the customer materials such as reviews and survey responses, online and social media.

Deep Learning

Deep learning is a study of Artificial neural networks with applications in image processing and other complex tasks that simple machine learning algorithms may not directly perform.

  • Neural Networks: These are algorithms that attempts to identify underlying relationships in a set of data by using a process that mimics the way the human brain operates. They have the ability to adapt to changing inputs without the need to redesign the output criteria
  • Semantic Learning: These are models that are utilized in developing intelligent systems that comprehend Language. Semantic networks themselves are utilized to store and retrieve knowledge.
  • AI Bots: These are computer programs which conducts a conversation via auditory or textual methods. These are designed to convincingly simulate human behavior as a conversational partner. They can use advanced AI techniques.

Our Artificial Intelligence Services

  • Consulting – Our Consulting offering comes with expertise in mapping business problems to technical solutions that ensure Business value attainment. We specialize in High level architecture, platform and design consulting for a large-scale data Processing, transformational BI and Predictive Analytics.
  • System Integration – Our System Integration Services focus on building custom analytical systems that are performant, efficient data management and maintenance of the cluster infrastructure that optimally utilizes a given computing environment.
  • .Solution Development – Our Solutions offerings come with a framework/Toolkits for solving challenges in a specific vertical or a domain. They would work on large datasets, variety of data structure and/or latency. These are complete solution builds that fits in well with customer’s Data Product strategies. We will utilize the open source accelerators that were built by us.
  • SupportOur RapidMiner Support offering is unique in terms of sharing our years of expertise working in the areas of Big Data Analytics and Data Science. We would put our experience to benefit nascent Data Science practices ramp up quickly on the Advanced Analytics journey or establish a captive support center.

Global Solution Partner

RapidMiner is the industry’s #1 open source data science platform, disrupting the market by empowering enterprises to include predictive analytics in any business process—closing the loop between insight and action. The platform makes predictive analytics lightning-fast for today’s modern analysts, radically reducing the time to unearth opportunities and risks.

Tools & Technologies

We leverage the following tools and technologies related to BI and Big Data in implementing the solutions.

Featured Case Studies

Digital Transformation of Tele-Medicine

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80% Reduction in Reporting Time
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IoT based Authentication Solution

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Combat $1.2 Trillion Global Counterfeiting Problem
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AI based Chatbot

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An Asia based automobile dealer saved over $1 M in customer service expenses

Self-Service Mobile App

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International automobile dealer increase customer service resolution by 50%

AI for Lending

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Global lending firm reduced operating costs & enterprise risk by using AI

Predictive Marketing Analytics

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US based large education provider increased lead acquisition and conversion rate using AI

Financial Fraud Analytics

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Global financial firm builds a strong fraud detection strategy to safeguard customers

IoT Analytics

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US based heavy equipment rentals agency improved equipment utilization and saved costs

Sales Forecasting

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Global E-commerce store achieved optimized pricing and identified candidates for various forecasting techniques

Service Center Analytics

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Global BPO Improved customer retention by analyzing the customer interactions using ML And NLP