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DataHarvest.AI

Welcome to Xmplar's Analytics & AI, where innovation meets excellence in harnessing the power of artificial intelligence to drive business transformation. With over a decade of experience in delivering top-notch products and services in the ERP and process automation space, Xmplar is dedicated to bringing substantial benefits to SME customers. Our latest AI offerings are designed to revolutionize the way you manage data, interact with customers, and optimize your supply chain.

DataHarvest.AI

dataxtract-automative

Automate Invoice Capture

AI-powered solution streamlines and automates accounts payable operation by extracting invoice data and importing it into an ERP system

Challenges of Manual Invoice Processing

Human Error

Typos and mistakes can lead to inaccurate financial records.

Time-Consuming

Manual entry demands substantial resources and time.

Lack of Transparency

Susceptible to manipulation and potential fraud.

Delayed Processing

Slows down invoice approval and payments.

Limited Scalability

Hinders business growth and efficiency.

challanges

Our AI-Enabled Solution

Xmplar’s Invoice Automation transforms invoice management by leveraging AI to automate data extraction from PDF or Image of invoices, integrating this data into ERP systems for seamless financial accounting. This solution handles various invoice types, such as IT services, travel expenses, and more, ensuring adherence to company spending policies.

Extract

Extract Tabular data from invoices in various formats like PDFs , spread sheet and scanned images

Understand

Identify pertinent data and entities from extracted invoice information

Validate

Rule-based checks on extracted data to ensure it is clean and error free

Transform

Bring the extracted data into a format consumable by downstream analytics and ERP system

Key Benefits

Effortless Intake

Easily upload invoices from multiple channels.

Out-of-Policy Detection

Flags potential non-compliant expenses.

Intelligent Preprocessing

Advanced PDF-to-text conversion maintaining data integrity.

ERP Integration

Seamlessly integrates extracted data into existing ERP systems.

Advanced Data Extraction

AI-powered extraction engine accurately captures key invoice data.

Data Visualization & Analytics

Supports insightful financial reporting and data-driven decisions.

Technical Highlights

technical
Unlike traditional AI models that require training with sample documents and fixed formats, our solution extracts printed and handwritten text from images and documents using generative AI. Optimized for financial documents, it accurately digitizes text from various business documents regardless of fonts, layouts, or languages.
Utilizes OpenAI and other LLMs for precise data extraction.
Ensures accuracy and reliability of extracted data.
Offers scalability, reliability, and security.
Features a user-friendly interface for finance teams.

Conclusion

Xmplar’s Invoice Automation modernizes invoice processing with advanced OCR, AI, and seamless ERP integration.

Enhanced Efficiency

Automates financial workflows for accuracy and compliance.

Superior Decision-Making

Supports better financial decisions and business growth.

conclusion
logistics

Logistics Document Extraction

Effective logistics data management is critical in navigating supply chain uncertainties and mitigating risks, especially in the wake of the COVID-19 pandemic. Accurate and timely data handling is essential for smooth inventory movement and business profitability.

Challenges in Logistics Data Management

Variability in Data Sources and Formats

Diverse document formats complicate data extraction.

Complexity and Volume of Documents

Managing a large number of documents manually is labour-intensive and error-prone.

Manual Data Entry

Leads to delays, inefficient resource allocation, and missed optimization opportunities.

challanges

Our AI-Enabled Solution

Xmplar’s AI-powered software automates the extraction of data from shipping and logistics documents, integrating seamlessly with ERP and analytics applications for real-time inventory tracking and analysis. This streamlines logistics operations, improves data accuracy, and enables informed decision-making to optimize supply chain performance.

Document Ingestion

Key Fields Extraction

Tabular Formating

Downstream Integration

Data Visualization & Analytics

Key Benefits

Increased Efficiency

Automates data extraction, reducing time and effort in logistics management.

Optimized Resource Allocation

Provides insights for better resource allocation, minimizing stockouts and excess inventory.

Improved Accuracy

Utilizes state-of-the-art Large Language Models (LLMs) for precise data extraction.

Enhanced Decision-Making

Offers comprehensive analytics and visualization tools for trend analysis and process optimization.

Real-Time Visibility

Integrates with CREST and Power BI for real-time inventory tracking and monitoring.

Technical Highlights

technical
Uses advanced AI functionality by leveraging a comination of LLM’s and vision models to extract printed and handwritten information from various logistics document formats with high accuracy.
Extracts key information from documents without the need for updating pre-configured templates, the AI model does not require retraining and maintenance
Utilizes advanced post-processing techniques to convert extracted data from various formats into a structured or semi-structured format
Seamless integration with CREST, Power BI, and other tools for inventory management and analysis.

How It Works

Document Ingestion

Ingests various formats of shipping and logistics documents.

Data Extraction

Uses Gen AI powered OCR, NLP, and computer vision for accurate data extraction.

Tabular Data Conversion

Converts extracted data into a structured format for analysis.

ERP and Analytics Integration

Integrates with ERP and analytics applications for real-time tracking and analysis.

Analytics and Visualization

Provides tools for in-depth analysis and visualization of logistics data.

Conclusion

Xmplar’s AI-enabled software revolutionizes logistics management by automating data extraction from shipping documents.

Data Accuracy

Enhances accuracy and streamlines operations

Real-Time Insights

Optimizes supply chain performance for competitive advantage.

conclusion
cc-statement

CC Statement Analyzer

Automate the extraction and comparison of credit card statements for accurate expense tracking and allocation.

Challenges in Credit Card Statement Reconciliation

Labor-Intensive

Manual comparison and reconciliation are resource-intensive and slow.

Error-Prone

High risk of inaccuracies and financial discrepancies.

Complex Expense Classification

Difficulty in consistently categorizing business expenses.

Inefficient GL Allocation

Manual allocation of expenses to GL accounts is cumbersome.

challanges

Our AI-Enabled Solution

Xmplar’s CC Statement Analyzer automates the extraction of data from credit card statements and supplier invoices, compares them, and structures the data for seamless integration into accounting systems. This solution reduces manual effort, enhances accuracy, and improves financial efficiency.

Key Benefits

Automated Data Extraction

Efficiently extracts data from credit card statements and invoices.

GL Account Allocation

Allocates expenses to the appropriate GL accounts, streamlining accounting processes.

Accurate Comparison

Uses AI to match transactions with corresponding invoices, ensuring accuracy.

Reduced Manual Effort

Minimizes the need for manual reconciliation, saving time and resources.

Expense Classification

Automatically classifies business expenses into relevant categories.

Technical Highlights

technical
Our Generative AI-powered OCR can accurately extract data from various credit card statement and invoice formats, including both printed and handwritten text.
Utilizes AI to compare and match credit card transactions with supplier invoices, ensuring precise reconciliation.
Leverages AI to classify expenses into business categories automatically.
Allows users to customize validation criteria, highlighting discrepancies for manual review.
Easily integrates with your accounting systems, ensuring smooth data transfer and processing.

How It Works

Document Ingestion

Upload credit card statements and supplier invoices via a user-friendly interface.

Data Extraction

Uses Gen AI-powered OCR and document parsing algorithms to extract key data fields from documents in a structured format.

Automated Comparison

Matches transactions with invoices and highlights discrepancies.

Expense Classification

Classifies expenses and allocates them to the correct GL accounts.

ERP Integration

Seamlessly integrates structured data into accounting systems.

Analytics and Reporting

Provides tools for analyzing financial data and generating comprehensive reports.

Conclusion

Xmplar’s CC Statement Analyzer automates the reconciliation of credit card statements with supplier invoices for enhanced accuracy and efficiency.

Financial Accuracy

Ensures precise expense tracking and GL account allocation.

Improved Efficiency

Reduces manual effort and streamlines accounting operations.

conclusion
Industry Snapshot

Foam & Mattress Industry Solution:
Key Features

Manufacture of foams, and various consumer products out of them, such as mattresses, pillows etc. is essentially routine manufacturing activity. However, there are certain unique aspects to this industry, which makes adopting a good cloud ERP a wise decision.
Being a consumer product, the cost of branding, marketing, and distribution are very high. Therefore, manufacturers are constantly trying to control cost of production, without diluting quality, and protect their margins.

Inventory

- Product grade and stage wise stock visibility, without creating multiple SKUs for every grade, or stage - Comprehensive material planning - Automatic raw material indent to stores based on production plan

Procurement

Automatic Purchase Order generation, based on inventory levels

New

Production Scrap & Wastage

- Production planning based on Consolidated Sales Orders - Stage wise Production reporting (Latex preparation, to finished product -Production accounting simplified, with barcode sacn

New

Material Traceability

Barcoding for final despatch. Automated Batch number with Traceability.

Technical Highlights

Functional modules in CREST ERP cover the entire needs of an area of operation of a business, such as Sales, Purchasing, Manufacturing etc. These modules are interconnected and interdependent, making it a seamless application user experience.

Unlike traditional AI models that require training with sample documents and fixed formats, our solution extracts printed and handwritten text from images and documents using generative AI. Optimized for financial documents, it accurately digitizes text from various business documents regardless of fonts, layouts, or languages.
Utilizes OpenAI and other LLMs for precise data extraction.
Ensures accuracy and reliability of extracted data.
Offers scalability, reliability, and security.
Features a user-friendly interface for finance teams.
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