AI Data Science

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AI Data Science

Data Science Capabilities

  • Enhance data extraction and perform several pre/post-processing actions.
  • Cognitive processes that can process unstructured and semi-structured data to power intelligent automation of end-to-end processes.
  • Machine Learning / Natural Learning Process, Crowdsourcing AI to get truly intelligent automation.
  • Own AI engine, such as a natural language processing (NLP) engine, to automatically compare extracted data against an existing database for verification.
  • Rapidly build custom AI capabilities that are available for any business user to deploy, Focused on artificial intelligence and cognitive automation.
  • Rapid build on Documents that are preprocessed (crop, noise reduction, etc.), indexed, and classified by the intelligent document classifier. These classified documents are then sent for data extraction by OCR based on type: fixed format (such as ACORD or UB-04) or variable format (such as invoices, purchase orders, etc.).
  • Full capabilities of automatic layout analysis, field recognition on paper, and compatibility with multiple languages and document types.
  • AI-driven extraction capabilities for more than 30 common business document types, including invoices, purchase orders, insurance claims, mortgage forms, bank statements, and explanation of benefits.
  • Intelligent automation — the integration of AI, machine learning, and RPA. Next era of automation and, when combined with artificial intelligence (AI).
  • Analyses were needed, run the data through a custom AI analytical model written in Python.

Core Areas of Artificial Intelligence Expertise

Building Solutions – AI/ML/NLP

Core Areas of Artificial Intelligence Expertise

Resume Screener for Recruiters

Resume screening is the process of determining whether a candidate is qualified for a role based his or her education, experience, and other information captured based on the requirements for a job.

Service Technicians Geo Fencing

Technicians appointments are captured and are plotted in a map. Wherever the technicians move the locations are tracked and the maps are optimized with routes.

Sensor Data Analysis and Modelling

Analyzed the Sensor data for various data insights and did prediction for next quarter with the utility bills.

Process for AI-Business Improvement

4. Natural language Interaction

Tell a software application to generate a report on sales revenue predictions without having to run the reports yourself

5. Natural language generation

Get summaries of everything that has been analyzed from a large document collection.

1. Pattern recognition

Understand trends for customer financial transactions and spot deviations to identify potentially fraudulent behavior.

3. Cognitive search

Offer personalized recommendations to shoppers by matching their interests with other customers who purchased similar items.

2. Prediction

Capture short- and long-term variability in data to improve forecasting

6. Innovative & Adaptive

Company experiments becomes intentional while executing at more promising & capable levels