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AI-Enhanced OCR Feature Development

A leading real estate company sought to enhance its custom Enterprise Resource Planning (ERP) web application by integrating an advanced Optical Character Recognition (OCR) feature. The primary objective was to automate invoice data extraction and streamline document processing, including integration with DocuWare and the Meylly addon for PDF upload and management.

 

Key Challenges

  • Manual Data Entry: The existing process required significant manual effort, leading to inefficiencies and potential errors.
  • Integration Complexity: Seamlessly incorporating the OCR feature with existing systems like DocuWare and the Meylly addon presented technical challenges.
  • Data Quality Assurance: Ensuring the accuracy and reliability of extracted data was critical.
  • Scalability: The solution needed to handle increasing volumes of documents as the company grew.
  • Cost-Effective AI Model Training: Developing and training AI models within budget constraints was essential.

 

Our Solutions

  • Efficient Document Processing: Developed an AI-enhanced OCR system to automate data extraction from invoices, reducing manual intervention.
  • Improved Data Accuracy: Implemented validation mechanisms to ensure the precision of extracted information.
  • Streamlined Workflow: Integrated the OCR feature with DocuWare and the Meylly addon, facilitating seamless document management.
  • Scalable Solution: Designed the system to accommodate growing document volumes, ensuring long-term viability.
  • Cost-Effective AI Training: Utilized efficient training methodologies to develop robust AI models within budget.

 

Tech Stack

Conclusion

The implementation of the AI-enhanced OCR feature significantly improved the company’s ERP application by automating document processing, enhancing data accuracy, and streamlining workflows. The scalable and cost-effective solution positioned the company for future growth, exemplifying the successful integration of advanced AI technologies into existing systems.

 

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Project Overview

IIFL, a leading financial institution in Asia-Pacific, required a solution to help customers track their income, expenses, and investments effectively. Our team developed an AI-powered mobile app that utilizes intelligent technologies like AI and ML to monitor financial transactions, suggest lucrative investment options, and provide insightful financial guidance.

Key Challenges

IIFL, a leading financial institution in Asia-Pacific, required a solution to help customers track their income, expenses, and investments effectively. Our team developed an AI-powered mobile app that utilizes intelligent technologies like AI and ML to monitor financial transactions, suggest lucrative investment options, and provide insightful financial guidance.

Our Solutions

IIFL, a leading financial institution in Asia-Pacific, required a solution to help customers track their income, expenses, and investments effectively. Our team developed an AI-powered mobile app that utilizes intelligent technologies like AI and ML to monitor financial transactions, suggest lucrative investment options, and provide insightful financial guidance.

Tech Stack

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Conclusion

In conclusion, SOMPO Insurance has successfully addressed the challenges of providing seamless insurance experiences and supporting both D2C and B2B journeys. Through the development of a comprehensive Customer Web Portal and integration with key services and platforms, SOMPO Insurance has demonstrated its commitment to innovation and customer satisfaction in the insurance industry.

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FRANCE

74 boulevard du, 11 novembre 1918 69100 villeurbanne

UAE

Office A-503, B-503 Sama Tower, Sheikh Zayed Road, Dubai, UAE

South Africa

Cube Work Space. 24 Hans Strijdom Avenue, Cap Town

UK

Kem House 160 City, Road, London, United Kingdom EC1V2NX

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Ahemdabad

Ahmedabad, INDIA

401, One World West, Nr. Ambli T-Junction 200,S P Ring Road, Bopal, Ahmedabad, Gujarat 380058, India

FRANCE

FRANCE

74 boulevard du, 11 novembre 1918 69100 villeurbanne

UK
UK
Kem House 160 City, Road, London, United Kingdom EC1V2NX
UAE

UAE

Office A-503, B-503 Sama Tower, Sheikh Zayed Road, Dubai, UAE

South Africa

South Africa

Cube Work Space. 24 Hans Strijdom Avenue, Cap Town

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