What is iKapture?
iKapture is an accounts payable automation platform that leverages Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and human intelligence to streamline invoice processing. It operates in a no-code environment, making it accessible and easy to integrate with existing ERP systems via API.
The platform offers a comprehensive solution for automating accounts payable, from document collection and classification to invoice matching and fraud detection. iKapture centralizes governance and prioritizes stringent security providing authentication methods.
Features
- Smart Access: Automated document collection and classification from multiple sources (PDFs, JPGs, PNGs).
- Document Classification: AI/ML-driven classification of various invoice types (tax, credit, commercial, legal).
- Role Based Access: Controlled access for different user roles (AP user, Manager, Finance Head).
- Authentication: Secure access with SSO and MFA for external users.
- Matching: Automated 2-way and 3-way invoice matching with purchase orders and goods receipt notes.
- non - PO: Processing for non-purchase order invoices.
- 360-Degree Visibility: Centralized invoice tracking, communication, and activity monitoring.
- Durusta – A Conversational BOT: AI-powered digital assistant for data retrieval.
- Fraud Detection: Rule-based and AI/ML-based techniques to identify fraudulent invoices.
- Supplier Segmentation: Categorization of suppliers for improved relationship management and risk assessment.
Use Cases
- Automating invoice data entry and processing
- Improving accuracy in accounts payable
- Reducing invoice processing time and costs
- Enhancing supplier relationships through timely payments
- Detecting and preventing invoice fraud
- Streamlining accounts payable workflows
- Integrating accounts payable data with ERP systems
- Gaining real-time insights into accounts payable performance
Related Queries
Helpful for people in the following professions
iKapture Uptime Monitor
Average Uptime
99.63%
Average Response Time
1806.8 ms
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