FEATURES

Data Cleansing

Data standardisation & AI/ML led data cleansing

Data
Enrichment

Enrichment from unstructured data sources, proprietary and 3rd party sources

Hierarchy
Management

Automated hierarchy mapping & ML based master data categorization at scale

Data
Quality

ML based automated anomaly detection for hierarchies, categorical and numeric data types

Data
Oversight

ML based ongoing data management to ensure continuous data quality management

Optical Character Recognition

Leverage the power of ML algorithms to digitize paper/pdf invoices, eliminating tedious data entry job

Domain Expertise

Deep understanding of Supply chain, procurement and finance

ML Based Reconciliation

Machine Learning based matching algorithm that actively learns and improves, reduces manual intervention

RPA Compatible

Efficient automation of existing processes by integrating with RPA tools

Insights Alerts Notifications

Configurable Workflow to send alerts/notifications to users, dashboards provide valuable business insights

Integration with ERP

Integrates seamlessly with existing ERP applications like Oracle, SAP, NetSuite, etc.
  1. AP Invoice Reconciliation: Seamlessly match Invoice details with Purchase Order and Goods Receipt Note (2/3/4way match) to reduce cost and effort to process invoices
  2. Freight Audit: Validate Invoice attributes to detect anomalies and democratize audit reports for quick decision making
  3. Cash Application Process Automation: Reconcile payments received via multiple sources remittance information and invoices thus reduce Time to Process payment information
  4. AR Sales Order Reconciliation: Reconcile Sales Order against Invoice and Purchase Order to reduce DSO (days sales outstanding)
  1. AP Invoice Reconciliation: Seamlessly match Invoice details with Purchase Order and Goods Receipt Note (2/3/4way match) to reduce cost and effort to process invoices
  2. Freight Audit: Validate Invoice attributes to detect anomalies and democratize audit reports for quick decision making
  3. Cash Application Process Automation: Reconcile payments received via multiple sources remittance information and invoices thus reduce Time to Process payment information
  4. AR Sales Order Reconciliation: Reconcile Sales Order against Invoice and Purchase Order to reduce DSO (days sales outstanding)

Customer MDM with Cognitive RPA

Enabling a unified and cleansed customer master across the enterprise by integrating multiple CRM systems

Product Hierarchy Management at Scale

Enabling development of product master data by standardizing taxonomy and cleansing data from different suppliers/retailers

Contact MDM with External Data

Enabling better marketing effectiveness through cleansing and 3rd party data enrichment of contact data systems

Product Attribute Enrichment with Computer Vision

ML tools & algorithms to extract attributes from images of multiple formats and enrich existing product attribute master data

Vendor Data Quality Management

Enabling unification of vendor database through cleansing, hierarchy & data quality management

Material Master Data Management

Enabling unification of material level master data through cleansing, hierarchy & data quality management
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USE CASES
  1. AP Invoice Reconciliation: Seamlessly match Invoice details with Purchase Order and Goods Receipt Note (2/3/4way match) to reduce cost and effort to process invoices
  2. Freight Audit: Validate Invoice attributes to detect anomalies and democratize audit reports for quick decision making
  3. Cash Application Process Automation: Reconcile payments received via multiple sources remittance information and invoices thus reduce Time to Process payment information
  4. AR Sales Order Reconciliation: Reconcile Sales Order against Invoice and Purchase Order to reduce DSO (days sales outstanding)
  1. AP Invoice Reconciliation: Seamlessly match Invoice details with Purchase Order and Goods Receipt Note (2/3/4way match) to reduce cost and effort to process invoices
  2. Freight Audit: Validate Invoice attributes to detect anomalies and democratize audit reports for quick decision making
  3. Cash Application Process Automation: Reconcile payments received via multiple sources remittance information and invoices thus reduce Time to Process payment information
  4. AR Sales Order Reconciliation: Reconcile Sales Order against Invoice and Purchase Order to reduce DSO (days sales outstanding)

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