A Data Contextualization Engine Powered by AI

Convert unstructured data into contextualized information for actionable business insights

Enterprise-grade Cognitive Data Capture and Processing Platform

WNS Skense ingests data (both structured and unstructured), applies proprietary algorithms to generate contextualized information, and finally summarizes to create structured and harmonized data sets for business analysis. This automated data processing engine is powered by advanced Artificial Intelligence (AI) / Machine Learning (ML) techniques that provide businesses with quick, accurate and actionable insights.


Features of WNS

WNS Skense is scalable, flexible and easy-to-deploy.
It simplifies data management across the three core dimensions of volume, variety and veracity.

Advanced Data Capture

Real-time data ingestion using custom connectors or Application Programming Interfaces (APIs)

Wider coverage of documents - TIFF, PNG, PDF, DOC, XLS

Al & ML Led Intelligence

Customizable business rules, AI / ML models and ontologies to drive contextualization

Serverless deployment of ML models enabling high availability and ability to auto scale

Scalable Deployment

Fully scalable and platform agnostic

Customized Usability

Intuitive User Interface (UI) for human validation and customizable workflow

Built-in workflow visualization

Self-service features

Automated Reporting

Integrated decision engines and analytical models

Ability to Manage Complex Documents
Across Diverse Industries

WNS Skense automates the extraction, organization, cleansing and interpretation of data in any format and in large volumes.

Healthcare Claims


Restaurant Menus


Insurance Binders




Accord Forms


Medical Reports


Airway Bills (AWB)

Bills (AWB)

Customs Declaration Forms

Declaration Forms


An Intelligent Engine with Self-learning Capabilities

WNS Skense works as a digital intelligent store combining data formats, domains, output formats and target systems to deliver significant value across the enterprise.

Improves ROI on investments in data science capabilities and tooling

Minimizes organizational risk arising from being people / system dependent or running siloed intellectual property

Reduces cost of operations by 40-60 percent in steady state

Improves ability to detect common data issues

Enables application of business rules on a harmonized output format for subsequent processing

How WNS Skense Works

Real-time Data Ingestion

  • Use custom-built APIs to drive effective data acquisition

Document Classification

  • Categorize data into key groups of information
  • Convert data into a machine readable format

Automated Processing

  • Identify, extract and classify data


  • Contextualize and summarize details into relevant categories of information
  • Use a centralized dictionary of ontologies and linkages for decision engine

Integration with Target System

  • Sync customized interface with relevant systems through API access


Cost savings of $50Mn for a large FMCG company using cognitive data management for aligning quality assurance and product supply operations to product life cycle management and GxP specifications

A Tried
- and -


Underwriting optimization by ~50% and overall accurancy levels of 85%+ for a leading broker in Lloyd’s of London through ML and Deep Learning (DL) led automated data extraction


Cost savings of ~$9Mn over 5 years, with an ROI of 16x (yearly volume of 270 million documents) through automated classification of shipment documents, followed by relevant information extraction


Financial Services

Processing time reduction by 50% and cost containment by 25-30% for a US regional bank using ML-driven financial spreading