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What is Ultra OCR?

With the help of Ultra OCR®, we proficiently extract text from a wide array of document formats. Robotic Process Automation (RPA) enhances this process by collecting data from various sources, including websites, public databases, and older systems or ERPs. Following this, Nuveo's cutting-edge Natural Language Processing (NLP) and Machine Learning (ML) technologies thoroughly analyze and interpret the collected information, drastically reducing the time spent on manual document analysis. Once the data has been assessed and structured, RPA or customized interfaces effectively channel the pertinent information into various systems or ERPs, facilitating a completely automated workflow. Nuveo’s patented Ultra OCR® is recognized as a top-tier solution for recognizing characters, words, and terms in images or PDFs, bolstered by advanced image processing algorithms that achieve recognition efficiencies that surpass industry norms. The incorporation of Machine Learning (ML) and Natural Language Processing (NLP) equips our system with the ability to learn, comprehend, and make well-informed decisions based on the documents it processes. As the volume of data increases, the system's accuracy and dependability consistently enhance, affirming the power of our pioneering technology. In essence, this robust integration of OCR, RPA, NLP, and ML not only streamlines workflows but also ensures that organizations can make smarter decisions faster.

What is Aquaforest Kingfisher?

Aquaforest Kingfisher streamlines the process of retrieving and organizing essential business information stored within PDF files, which include various types of documents such as financial statements, client reports, scanned images, and records of payments. It offers automated features for intelligent data extraction, document splitting, and renaming, as well as optical character recognition capabilities to effectively manage image-based PDF files. Users can easily convert the extracted content from PDFs into formats like CSV, Excel, or simple text files. All of our solutions are designed to work seamlessly within virtual environments, particularly with Oracle VM VirtualBox. The subscription includes comprehensive support and ongoing maintenance for the duration of the service. A skilled engineer is on hand to remotely install and configure Aquaforest Kingfisher according to your specific requirements. This installation takes place on a separate machine from the SharePoint server, facilitating a smooth integration process. Additionally, the support for the Windows File System allows for the preprocessing of documents before significant data migrations take place. Users can also choose to extract PDF pages based on their content or utilize barcode identifiers, which further enhances the flexibility and efficiency of the data extraction process. This thorough methodology guarantees that businesses can effectively manage, leverage, and maximize the use of their critical information for strategic decision-making. By optimizing data handling, organizations are positioned to drive innovation and improve operational productivity.

Media

Media

Integrations Supported

Integrations Supported

Microsoft 365
Microsoft Excel
Microsoft SharePoint
Oracle VM

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

€410 per year
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

Windows

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Nuveo Technologies

Company Location

Canada

Company Website

www.nuveo.ai/

Company Facts

Organization Name

Aquaforest

Company Location

United Kingdom

Company Website

www.aquaforest.com/products/kingfisher

Categories and Features

Data Extraction

Not specified

Categories and Features

Data Extraction

Not specified

PDF

Not specified

PDF Splitters

Not specified

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