Enterprise checklist to find the best OCR software

Finding a good OCR software can be a difficult task as it involves many critical aspects.

Please note that this content is not intended to make a statement about which OCR software is the best. Rather, it is intended to provide you with a framework within which you can evaluate and compare OCR software for yourself. The goal of this framework is to give you the tools you need to make an informed decision about which OCR software best meets your organization's needs. Using this framework, you can review and compare OCR software to ensure it meets your organization's needs and delivers the results you want.

Overview of OCR software functions

The OCR software must have a robust data processing pipeline that can accurately extract and process data from multiple sources. It should also have powerful content digitization capabilities to ensure a seamless and efficient digitization process.

In addition, the software should have a high level of document understanding in order to correctly interpret the content of the document. This is important for the software to deliver accurate results. Also, a good OCR software should have a user-friendly interface and be easy to use to ensure smooth usage.

Data cleansing and formatting are also important components to consider when selecting OCR software. The software should be able to effectively cleanse and format data to ensure data quality and consistency. In addition, data storage and management features are important to ensure secure storage and retrieval of data.

Finally, the OCR software should have robust operational and monitoring capabilities to ensure smooth operation and avoid downtime or errors.

Finding a good OCR software requires a careful evaluation of all the above categories, and it is important to choose a software that meets the specific needs of your business.

Data Processing

The data processing pipeline is an essential component of Document AI, OCR, and IDP software vendors as it provides the infrastructure for managing, processing, and delivering the software output to the end user. The requirements listed above ensure that the pipeline has robust and flexible capabilities for data input and output, processing accuracy and exception handling, integration with internal and external systems, collaboration, monitoring and reporting, and user control and security. These features are important for delivering reliable, efficient, and easy-to-use software solutions to customers and businesses.

5 questions to ask your OCR software provider

When evaluating Document AI, OCR or IDP software vendors, it's important to understand their capabilities and features in detail to determine if they meet your needs. Here are the top 5 questions you should ask vendors:

1. Does the software learn from new documents and how does it handle errors and exceptions during processing?
2. Can your software integrate with our existing internal systems and external software such as RPA or cloud platforms?
3. How does your software handle user collaboration, input control, and security in processing pipelines?
4. What kind of reporting and monitoring options do you offer to track the performance of our pipelines and ensure they are running efficiently?
5. Can you provide examples of similar projects you have worked on in the past and their results, as well as references from other customers who have used your software?

Content Digitization

The requirements listed under content digitization are mandatory for providers of Document AI-This is important for the OCR, OCR and IDP software as it determines the scope of documents and data that can be processed by the software. The ability to perform forced OCR on all incoming documents ensures that scanned or image-based documents can be processed. The ability to process a variety of file types, including emails, Word documents, PDF files and images, extends the range of input that the software can process. With the ability to process tables, extract form data and split documents into smaller components, the software can extract specific data from complex documents. The key-value pair extraction feature is important for extracting relevant information from documents and making it searchable and accessible for further analysis and use. These features are critical to providing a comprehensive digitization solution for businesses and organizations.

5 questions to ask your OCR software provider

When evaluating the content digitization capabilities of a Document AI, OCR, or IDP software vendor, it's important to ask questions that challenge the vendor's capabilities and ensure their software meets your needs. Here are 5 questions you can use to question content digitization capabilities:

1. Can your software handle large volumes of incoming documents and process them in a timely manner?
2. Can your software accurately and consistently extract data from tables and forms in documents?
3. How accurate is your OCR technology and what measures are in place to correct errors and handle exceptions during processing?
4. Can your software break large documents into smaller, more manageable components and extract specific data from them?
5. Can your software extract and process information in different languages and handle multilingual documents?

Document Understanding

Key features that document understanding software should have include the ability to classify and sort documents based on type, flexible extraction of elements, recognition and normalization of numeric, date, currency and address information, checkbox recognition, confidence level and accuracy assessment, detection and minimization of irrelevant information, support for multiple languages, special recognition for insurance-related documents, identification of signatures and signatories, recognition of "strikethrough" text, extraction of attributes and document structure, extraction of relationships and entities, recognition of named entities, NLP-based recognition of exclusion cases, multi-layer extraction logic, recognition of missing mandatory fields, and Recognition and extraction of comments from Adobe PDF documents.

5 questions to ask your OCR software provider

When evaluating a software vendor's document understanding capabilities, it's important to ask questions that question the vendor's capabilities and ensure the software meets your needs. Here are 5 questions to challenge document understanding capabilities:

1. How accurate and reliable is the document classification and sorting mechanism? Can it be adapted to specific needs?
2. Can the software accurately and consistently recognize and extract data from different types of documents, including those with complex structures or formatting?
3. Can the software recognize and normalize number, date, currency, and address information, even in documents with inconsistent formatting?
4. How well does the software handle multilingual documents and can it accurately recognize and extract information in different languages?
5. Can the software identify and extract complex information such as clauses and exclusions, recognize comments, and detect missing mandatory fields?

User Experience & Usability

Ease of use is an important factor to consider when choosing the best OCR software, as it directly affects the efficiency, productivity, and accuracy of the extraction process. Here are some reasons why usability should be a major concern:

1. Speed and efficiency: Features such as smooth document loading and processing, WebSSO integration, and mass uploading of extraction fields help users work quickly and efficiently and improve their overall productivity.
2. Flexibility: Various annotation options and the ability to manually correct extracted data provide flexibility for users, allowing them to choose the methods that work best for them.
3. Accuracy: Features such as keyword search in the document, integration of UI and REST API as well as the ability to automatically approve or approve/reject AI recommendations in bulk, improve the accuracy of extracted data and reduce the likelihood of error.
4. Organization: Clear and organized extraction output, easy categorization and sorting, and the ability to distinguish between required and desirable extraction fields improve the overall organization of extracted data and make it easier for users to work with and understand.
5. Usability: Features such as zoom in/out, page navigation and document rotation improve the overall usability and make working with the software more pleasant and efficient.
6. Seamless integration: Seamless workflow integration with the user's existing processes improves the overall efficiency and productivity of the software and makes it easier for users to integrate it into their work.

16 factors for high usability of OCR software

By providing these features, OCR software can improve the overall usability and efficiency of the extraction process, becoming a valuable tool for users.

1. Document loading and processing time: Smooth and fast loading and processing of documents ensures a high level of user satisfaction and productivity, as users can quickly switch from one document to another without having to wait for the software to catch up.
2. WebSSO integration: Web Single Sign-On (WebSSO) integration allows users to access the software with their existing corporate credentials, saving time and reducing the number of passwords they need to remember.
3. Annotation options: Various annotation options, such as box selection, left-to-right clicking, or multiline annotation, provide users with flexibility in how they annotate documents and allow them to work in the way that is most convenient for them.
4. Keyword search within a document: The ability to search for keywords while annotating a document makes it easier for users to find relevant information and increases their efficiency and accuracy.
5. UI and REST API integration: The integration of the user interface (UI) with a backend database enables easy data selection and validation, improving the accuracy of the extracted data.
6. Output Preview Panel: An output preview panel provides users with a visual representation of the extracted data, allowing them to quickly identify errors or discrepancies and make corrections as needed.
7. Flexibility in correcting extracted data: The ability to manually correct extracted data improves the accuracy of the final output and provides better control over the extraction process.
8. Recommending the best possible selection: Recommending only the best possible selection instead of multiple options saves users time and reduces the likelihood of errors.
9. Automatic approval/rejection of AI recommendations: The ability to automatically approve or bulk approve/reject AI recommendations streamlines the extraction process and saves time.
10. Clean and clear extraction output: Clear extraction output makes it easier for users to understand and use the extracted data, improving the overall usability of the software.
11. Document navigation options: Features such as zoom in/out, page navigation, and page rotation make it easier for users to work with documents and improve the overall user experience.
12. ML approach: an ML approach that considers each input as a real-time training set, rather than updating the model periodically, improves extraction accuracy over time.
13. Seamless workflow integration: Seamless integration with a user's existing workflow improves overall software efficiency and productivity.
14. Required vs. "Nice-to-have" extraction fields: The ability to distinguish between required and "nice-to-have" extraction fields allows users to prioritize their work and improve the accuracy of the extracted data.
15. Bulk upload of extraction fields: The ability to bulk upload extraction fields using an Excel template saves time and reduces the likelihood of errors.
16. Easy categorization and sorting: The ability to easily categorize and sort extracted data improves the overall organization and usability of the software.

Data Cleansing and Formating

Data cleansing and formatting features are important in OCR software because they ensure that the extracted data is accurate and consistent and can be used in other systems. These functions facilitate the connection to CRM or ERP systems, because:

1. Improved data quality: Data cleansing capabilities help remove errors, inconsistencies, and duplicates from extracted data, making the data more accurate and reliable for use in other systems.
2. Consistent formatting: Formatting functions ensure that the extracted data is consistent and clear. This facilitates integration with other systems and reduces the likelihood of errors.
3. Increased efficiency: With clean and well-formatted data, it is easier to connect to other systems and automate data processing, reducing the time and effort required for manual data entry and minimizing the risk of errors.

In summary, the OCR software's data cleansing and formatting features help ensure that the extracted data is of high quality and consistent, which facilitates integration with other systems such as CRM or ERP systems and reduces the likelihood of errors. This ultimately saves time and improves overall efficiency and productivity.

5 questions to ask your OCR software provider

The following questions are important in selecting the best OCR software because they help determine the software's ability to extract and clean data accurately and efficiently. The features they address include field validation and standardization, table extraction and auto-fitting, custom regular expression validation, data masking, and Python script/API integration. These features ensure that the extracted data is consistent, accurate, and secure so that it can be more easily used in other systems.

1. Does the OCR software support validation and standardization of fields, such as conversion between US and EU date formats and different number formatting?
2. Can the OCR software extract tables from PDFs and adjust the rows and columns automatically?
3. Does the OCR software allow the use of custom regular expressions for data validation and cleaning after extraction?
4. Is the OCR software capable of masking or redacting sensitive or personal data?
5. Is it possible, Python scripts or connect to third-party APIs, such as the Google Maps API, for data validation in the OCR software?

Data Storage and Management

OCR software must have good data storage and management features as it ensures the efficiency, security and accessibility of the extracted data. Here's why:

1. Efficiency: Good data storage and management features help organize the extracted data so that it is easy to find, retrieve, and use. This can save time and increase efficiency in data processing and analysis.
2. Security: Proper storage and management of extracted data helps protect sensitive information from unauthorized access and ensures data privacy.
3. Accessibility: The ability to store and manage extracted data in a way that makes it easily accessible can be important for collaboration and sharing, as well as for future reference and analysis.

In summary, good data storage and management features are critical to ensure efficiency, security and accessibility of extracted data - all important factors to consider when selecting OCR software.

5 questions to ask your OCR software provider

Below are 5 questions you should ask to determine if the OCR software is best in class for data storage and management:

1. Does the software have machine-interpretable business rules and policies for data storage and management?
2. Can the software support taxonomy and knowledge graph curation to categorize and organize the extracted data?
3. Does the software have version control for similar or identical documents?
4. Does it have record versioning and logging to track changes and updates to the extracted data?
5. Can it integrate or interface with your archiving tool and provide simple search (semantic or faceted) or filtering capabilities for the extracted documents?

Operations and Monitoring

For large enterprises, evaluating OCR software for operations and management is critical to ensuring that the software meets their needs for efficient, secure, and scalable data processing and management. Here's why:

1. Efficiency: Efficient operation and management of OCR software can help reduce processing time and increase productivity, saving the company time and money.
2. Security: Proper operation and management of OCR software can help ensure the security and privacy of sensitive data and protect the organization from data breaches and other security risks.
3. Scalability: Large enterprises often process large amounts of data and need software that can scale to meet their needs. Evaluating the OCR software's operational and management capabilities can ensure that the software is suitable for the company's current and future data processing needs.

In summary, evaluating OCR software for operations and management is critical for large enterprises to ensure that the software is efficient, secure, scalable, and meets the organization's data processing and management needs.

5 questions to ask your OCR software provider

Below are 5 questions to ask an OCR software vendor to determine if the software offers top-notch operational and management features:

1. Does the software provide role-based access control at the document level to protect sensitive data and ensure compliance?
2. Does the software provide explanations for its machine learning models to understand how decisions are made?
3. How does the software manage the lifecycle of its machine learning models, including versioning and deployment?
4. Can the software detect and report any shifts in the data to ensure accuracy and prevent data drift?
5. Does the software provide reporting and analysis of extraction results and can it be audited against user logs?

OCR software automates data processing tasks

Optical Character Recognition (OCR) software can play a critical role for companies looking to digitize their paper-based data and automate their data processing tasks. Here's why:

1. Increased efficiency: By automating the process of extracting data from paper documents, OCR software can significantly reduce manual data entry and processing time, increasing efficiency and productivity.
2. Improved data accuracy: OCR software uses advanced machine learning algorithms to accurately extract and recognize text from images, reducing the likelihood of errors and improving data accuracy.
3. Enhanced security: OCR software can be configured with advanced security features to protect sensitive data, ensure compliance with data protection regulations, and reduce the risk of data breaches.
4. Scalability: OCR software is able to handle large volumes of data and meet the needs of growing businesses, so it can meet the data processing needs of organizations of all sizes.
5. Easy integration: OCR software integrates easily with other systems, such as CRM or ERP systems, so companies can streamline their data processing operations.

In summary, OCR software can help organizations automate their data processing tasks, improve data accuracy, enhance security, and support their data processing needs as they grow. When selecting OCR software, it is important to consider features such as data validation, extraction accuracy, and ease of integration to ensure that the software meets the needs of the business.