OpenText Intelligent Capture Reviews

OpenText Intelligent Capture offers valuable features like accurate extraction using machine learning, automated vendor invoice management reducing human involvement, and the ability to classify and identify document types automatically. Its powerful OCR tool supports scanning and image processing. Custom scripting enhances functionality for those with coding expertise. Easily integrated with CRM systems, it provides robust document management with multi-tenant access, permission control, and convenient access through API for email, mobile, and web.

• "The enterprise and capturing feature of OpenText is its valuable feature. As we have integrated CRM with OpenText."
• "The solution is very powerful because it allows for custom scripting."
• "It allows you to image capture, scan documents and use machine learning to automatically index and tie them."

OpenText Intelligent Capture's primary areas needing refinement include enhancing duplicate document detection using AI or security algorithms, implementing OCR capabilities for specific data extraction, and improving user-friendliness. Licensing costs present challenges for smaller businesses. The mobile capture feature also requires attention to improve smartphone efficiency. Additionally, more reporting capabilities and lightweight versions with OCR options, excluding extensive packages, are suggested. Further, concerns exist around handling handwritten documents and .NET knowledge necessity.

• "The area for improvement primarily centers around licensing concerns rather than technical issues. Captiva, intended for larger clients, poses challenges for medium and small businesses due to licensing costs. The current licensing model is based on volume, such as purchasing a volume for one million dollars per year for scanning. This pricing structure may be prohibitive for companies with constrained budgets. Another aspect requiring attention is the mobile capture feature, which, although experiencing recent enhancements in intelligent document processing through AI, could benefit from further improvements. Specifically, there is room for enhancement in enabling users to efficiently capture documents using their smartphones."
• "We are using it to improve the image and the documentation for the cases. And sometimes, some cases have more than fifteen different types. We use some tools as fixed standard analysis and provide information to support the different types to take some decisions and help in an automated process. We choose the case type and subtype DNS scanning documents from the data entry up."
• "Knowledge of .NET is required to effectively use the solution or it can be complicated."