Intelligent Document Processing (IDP) is a technology based on Artificial Intelligence (AI) and Natural Language Processing (NLP) to transform unstructured information from documents of various formats into data that is useful for the management of documents/data of a company.
Currently, companies have thousands of data in unstructured formats (e.g., PDFs, images, videos), and extracting and organizing information from these complex contents into actionable information is an arduous task if you do not have an IDP system.
That is why Intelligent Document Processing can automatically capture, extract and process data from documents of various formats thanks to Machine Learning. Also, thanks to Deep Learning models, an IDP system can remove information from structures such as images and videos.
What can be done with an Intelligent Document Processing system?
- Automatic classification of documents and contents, both documents in PDF, Word, Excel, etc., such as image and video formats.
- Thanks to Machine Learning, most of the processing is automated so that the user only uploads a document to the IDP-based platform, and it does the rest.
- Extraction of information, semantic analysis, and identification of elements and images in each document, among others.
- Indexing of audio from videos and podcasts
- Obtaining text from scanned documents (OCR)
- Extraction of texts and metadata from documents in different formats
- Advanced indexing of texts and images
- Obtaining tags from images
What advantages do you get from IDP?
- Save on document processing. The return on investment is obtained by saving labor and improving the quality of the results. For example, for companies in the construction sector or other sectors that generate large volumes of documents and need to manage them, such as classifying them, an IDP system works automatically.
- It allows the generation of new intelligence. In this case, the return on investment is not so much in the savings -but also- but in the enhancement of content and documents that, adequately treated, can generate new intelligence that adds value to the company’s activity. For example, in a law firm that wants new uses for the knowledge generated by the company and seeks to reduce the effort of sharing this knowledge.
- Advanced analytics to make the business effort profitable. Thanks to Our software’s advanced analytics, you can optimize and take advantage of your company’s document management.
- Custom development and dumping of data in the client’s system. Our IDP Solution is adaptable to the needs of each client; from DOCBYTE, we develop what our clients need. The platform also allows the data and outstanding opportunities to be transferred to the client’s document management system.
At DOCBYTE, we have developed a platform based on IDP and Artificial Intelligence (AI) that allows us to automate tasks related to managing and classifying documents, multimedia content, and files with other unstructured formats.
Thanks to AI and Natural Language Processing techniques, this IDP platform allows for extracting and indexing data and discovering knowledge, and detecting opportunities.
What else does the IDP platform offer?
- Early Warning System for the early detection of opportunities from potential opportunity search bots and their evaluation using Artificial Intelligence techniques.
- You can search for “what is said” in a video or objects that appear in the images of the video. Our IDP platform can locate this type of content through Natural Language Processing (NLP) techniques and Deep Learning models.
- Our IDP platform can recognize objects in images and generate tags. This allows you to search and create alerts on recognized objects in images and perform searches by image similarity.
- Related to the above, Our IDP platform can detect duplicate documents.
- In addition, it allows the creation of alerts so that you are informed of what is most relevant to you and your work, thanks to its intelligent alert system.
Ten key elements to keep in mind when hiring an IDP system
An IDP system must:
- Support content movement flows between the company’s different internal or external data repositories. Suppose we need to move some documents from a specific folder to storage in SharePoint; for this, a file movement flow can be defined. We will always need to move content between repositories, which should be done flexibly and efficiently.
- Allow the configuration of processing rules that can be chained and form processing flows. In the previous assumption, in addition to the movement flows, we also need processing, such as extracting data (tags) on the images we have in the repository. An IDP can carry out this configuration through processing rules.
- Also, allow the configuration of rules and notification flows through various channels. The IDP must provide notifications when there is a procedure of interest: suppose, with the previous example, that every time the system detects a person appearing in an image (processing), it notifies us with a notification via email (digital mailroom).
- Make possible the use of the company’s document management system(s) (e.g., SharePoint, Think Project, etc.). An IDP is complementary to the document management system. For this reason, it is important that it can be integrated with any document management system. Thus, as in the previous example, the result of the flows could end up being dumped into a SharePoint repository.
- It is feasible to define access levels or roles to document spaces and functionalities. The IDP system must have a flexible user management system to define user roles and access levels. For example, create a profile that can only upload documents or another shape with the rule editor role.
- Facilitate incorporation of new Artificial Intelligence models, including access to other third-party intelligence services. Artificial Intelligence and Natural Language Processing are evolving at a frenetic pace. To avoid being left behind, an IDP must allow the incorporation of new models or access to the latest cognitive services available.
- Make possible the incorporation of new access to data repositories through APIs, ETL, or other systems. What is valid today does not have to be tomorrow. We will always need to incorporate new data sources (both external and internal), and the IDP system must allow this. So, for example, we may discover a new open data API relevant to our organization, and the IDP must enable the incorporation of this new data.
- Include dashboards so that the administrator can evaluate the use of the platform through KPIs (metrics). Platform administrators need to have access to metrics on platform usage. The ideal way to do this is through a dashboard.
- Have an administration area to properly configure the platform by its administrators. As mentioned before, the IDP system is dynamic (new flows, processes, notifications, roles, etc.) and should have an administration area so that this management is easy to carry out.
- Allow developments on it. No matter how flexible a platform is, there will always be a need for ad-hoc development. Finally, one of the most relevant elements is that no matter how powerful the IDP platform is, we will always find use cases that will not directly support it. In these cases, we must check if hiring custom developments in the IDP system is possible to cover these use cases and that their price is not exorbitant. The more flexible the provider, the better. This will allow adapting any aspect of the IDP platform: new screens, new processing, new flows, etc.