Algodocs

export extracted data to excel

intelligent document processing

IDP Use Case: Transforming Restoration Practices

Earthquakes, hurricanes, mudslides, electrical fires, and burst pipes are some of the natural incidences that are usually unforeseen. Buildings that are often at the receiving end during catastrophic calamities require immense repair work. Any comprehensive structure will, in this respect, indeed call for disaster recovery management, especially if it is a house or a company. It has scaled tremendously to be vital software in the construction industry, but it is notably critical in the catastrophe repair industry, where most companies are small. Table of Contents: But as structures progress, many organizations like yours struggle to cope with change. Often, the driving force of success is in the technology that forms the basis of these organizations. Let us think of the building and restoration industry and see what we come up with. These companies have to estimate all possible costs for a building construction project, including additional costs such as salary for office employees, wear and tear of equipment, office rent and other overhead expenses, and cost of all the materials used and wages to workers. Enhancing Data Management in Restoration Processes Intelligent Document Processing (IDP) tools can capture information from any format that has not been pre-formatted, including images and handwritten writings. This can be of great importance, especially in restoration processes where data could be in large quantities, in the form of field notes and sketches, among other things. The Importance of Accurate Costs and Expenses Some of the factors one needs to understand well to accurately estimate the cost of the project include the building material costs, the requirements, the procedures, and the codes that are to be followed, as well as the need to understand the market trends in terms of pricing. Such information may be found by analyzing a bid package and working through the contingencies and profit inherent in a bid or a given project. Two Significant Challenges: Documentation obstacles: One of the challenges associated with restoration events is collecting all the relevant and non-concocted paperwork. Some of the effects of this cumbersome procedure include the failure to complete some forms or the delay in completing them. Accounts Receivable Delays are attributed primarily to fourteen struggles stemming from a high turnover rate in accounting: payment cycles take longer. This not only impacts cash flow but also definitely causes a lot of headaches for the business’s dealings with its customers. The Impact of Intelligent Document Processing (IDP) Software on Restoration Businesses: Implementing Intelligent Document Processing (IDP) Several Challenges. Here are some of the key ones: Case Study Use case for restoration: The repair company wishes to provide the customer with an overview of line-item estimates for the job. Cost estimates should not be utilized as a list of negotiable items. Supplemental costs may apply if more damage or repair that has not been found or is hidden below present finishes is required. This also enables the client to correct himself or herself if they chose compositions that are not within the estimate or if they need extra work. This is because, in the course of the project implementation, changes will be made to adjust for the revised estimate and present it to the client. Any changes made to these documents will be recorded in a change order and presented to the customer for revision. System: It is a form of advanced digital document processing with natural language processing, multimedia processes, and feature extraction. Primary actor: Accountant/bookkeeper/Customer Scenario: To meet the customer’s request to extract the estimated line-item information from the final amount, the following processes should be considered: They ask for the extracted data to be formatted differently than the original document’s formatting. They clearly explain what should be ignored and what needs to be extracted. There are a total of 11 headers in the PDF; each row value contains three different pieces of information: one is the labor, the second is the material, and the third is the equipment information. They need to extract the labor and material information. For example, the following are the instructions for the needed to be extracted data and how it should look like output: Tabular output with headers and the order they should be in JSON form: ·”ITEM#”, mapped from the label in Yellow (as in the picture above) ·”ROOM”, mapped from the label in dark green (as in the picture above) ·”UNIT”, mapped from the label in Red (as in the picture above) ·”QTY”, mapped from the label in light blue (as in the picture above) ·”UNIT PRICE”, mapped from the label in light green (as in the picture above) ·”TOTAL” mapped from the label in pink/magenta (as in the picture above) However, we still need to extract and differentiate data for Labor and Material information. While mapping the extracted data to the new headers, as requested by the customer. As complicated as it looks and sounds, Algodocs can do exactly this request easily.  How to Use Algodocs to Extract We only need a sample file uploaded to Algodocs to create the extractor. There are many ways to upload a sample document. The user can automate importing files to Algodocs uploading from their device, business email, Gmail, or other cloud storage. Once the documents are uploaded, the system will extract data from your documents using Algodocs’ advanced AI engine without relying on templates or even labeling and training your files.  The results are the actual contents extracted from the sample document according to the rules you specify. We have Rule-based extraction and artificial intelligence mining, which can be integrated to synthesize both extraction methods. This can help you further improve your extracted data by putting it into the correct form and structure.  The system makes it easy to control extracted data from your documents and handle business exceptions. It allows you to export the extracted data directly to an Excel Spreadsheet or, with the integration of Zapier, automate exporting extracted data directly to your email, Google Sheets, or other cloud storage. Example of Output in Excel Key Takeaways This should explain how Algodocs has boosted the restoration business and its experience with the solution to prove that technology can transform any business. Let your team be an example of how adopting effective and progressive concepts can

Data Extraction, PDF

What is a PDF Parser?

Back to Blog Table of contents On this page What is a PDF Parser? Home › Blog › Data Extraction › What is a PDF Parser? Categories Data Extraction PDF Tags ai platform for data extraction algodocs character recognition data extraction from images deep learning export extracted data to excel invoice process machine learning ocr api web-based ai platform for data extraction By Shubhankar Biswas Published October 13, 2025, 12:03 Updated July 29, 2026, 02:32 A PDF Parser is a program or a library that enables end-users and organizations to parse data from native PDF documents. Often, organizations need to parse PDF documents for specific fields such as Account Number, Date, Address, Bill to/from information, or parse tabular data. PDF Parsers are usually needed and used for processing and parsing data from large amounts of documents. On the other hand, when you have a handful of documents you simply go and copy the data you need from PDF documents manually and paste it to Excel or anywhere you need it to be. PDF Parsers enable end-users to get data from hundreds and thousands of PDF documents in real time by saving huge amounts of time and, thus, money. Parsing pdf documents isn’t an easy task. There are various ways native pdf documents are generated and parsing data from such pdf documents requires smart approaches. Parsed data from PDF documents greatly varies depending on the industry, which means the data parsed might also greatly change, which complicates the task. Parsing PDF medical forms, which contain specific fields such as First, Middle, and Last names, Sex, Date of Birth, etc. are very different from PDF purchase orders that contain mainly the items in the tabular form with such columns as Item No, Code, Quantity, Item Price, Amount, etc. Therefore, if PDF Parser produces just a bunch of text from a PDF document it does not make much sense for the end-user. What end-users or organizations require is the structured data parsed from PDF documents. In other words, PDF Parser should extract from PDF documents only the data the end-user needs and in the right structured format. For this, the PDF Parser must be smart and flexible enough to parse PDF documents with various layouts and data types. How to parse PDF documents with various layouts? Algodocs allows you to parse PDF documents of any complexity in their layouts and type of data. With the flexible extracting rules of Algodocs, you can parse data from PDFs with different layouts. It is very easy and quick to set up extractors in Algodocs for your PDF documents. We provide 100% free technical support and are ready to set up extractors for you. While we provide free support for creating extracting rules, you may check our help and support section if you wish to learn how to create extracting rules in Algodocs. Watch the following introductory video to get an idea of how it works in Algodocs. Feel free to start a free subscription right now and parse your pdf documents. You can use Algodocs free forever with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. If you have specific requirements and need a custom solution, please contact us. You Might Also Like PDF Data Extraction: The Best Tool and Techniques PDFs are ubiquitous in every organization, serving as the go-to format for sharing and exchanging business data. However, extracting, editing, or… Shubhankar Biswas October 13, 2025 PDF Image Extraction: A Comprehensive Guide To Extracting Image Data From Scanned Pdf Files In 2025 PDF image extraction is a challenging process. Without proper tools and technology, this process can be tedious and prone to errors, which can… Shubhankar Biswas September 1, 2025 Convert PDF to JSON – Convert PDF Documents to Structured JSON Objects Table of Contents Introduction Organizations in various industries widely use PDF documents, since no doubt PDF is a common document format for… Shubhankar Biswas October 13, 2025 Start extracting your data today No credit card required. Process up to 50 pages per month on the Forever Free plan. Book a Demo Get Started for Free

PDF

Convert PDF to JSON – Convert PDF Documents to Structured JSON Objects

Back to Blog Table of contents On this page Convert PDF to JSON – Convert PDF Documents to Structured JSON Objects Home › Blog › PDF › Convert PDF to JSON – Convert PDF Documents to Structured JSON Objects Categories PDF Tags ai platform for data extraction algodocs character recognition data extraction from images deep learning export extracted data to excel invoice process machine learning ocr api web-based ai platform for data extraction By Shubhankar Biswas Published October 13, 2025, 11:59 Updated July 21, 2026, 05:15 Introduction Organizations in various industries widely use PDF documents, since no doubt PDF is a common document format for businesses to transfer data. Purchase orders, Invoices, Agreements, and many more document types are interchanged in PDF formats. On the other hand, JSON is another format that represents data in a structured format, which is widely used in transferring data between web applications. As a result, Working with JSON is much easier than with PDF. Therefore, in this article, we will talk about PDF and JSON formats and how you can convert your PDF documents to JSON format. What is a PDF? PDF (Portable Document Format) was initially developed by Adobe® Systems in 1992 and is standardized as ISO 32000. What makes PDF so popular is it is independent of the application software, hardware, and operating system. Other than text and images PDF files may contain a variety of content such as annotations, form fields, layers, etc. There are many advantages of PDF format such as multi-dimensionality, which we have already mentioned – being able to contain various types of content, text, images, videos, vector graphics, interactive fields, hyperlinks, and buttons. Moreover, PDF documents are easily created and viewed on different devices.  Security in PDF was one of the primary concerns of Adobe® Systems. Therefore, PDFs have different access levels to protect the content and the whole document, such as passwords, digital signatures, and watermarks. However, some of the downsides of a PDF are the complexity of editing and especially extracting data from it. Moreover, PDFs are not generated in the same way, so different PDF files can be created in various ways, which complicates the task of extracting data from PDF documents. What is a JSON? JSON (JavaScript Object Notation) is a very popular data format, which appeared in the early 2000s. JSON is a language-independent data format and is used to transfer data between software applications, particularly web applications, usually between server and client.  Most of the API integrations are realized using JSON format for data transfer since it is very easy to work with JSON. Consider a JSON object called person, which contains the following information:{   “name”: “John”,   “surname”: “Doe”,   “age”: 25} Accessing fields of a JSON object is as simple as using the name of the object and the field name you want to access by separating them with a dot as follows: To access a person’s name we use person.name, which will give us “John” as a result. Similarly, we do for surname and age fields: person.surname, person.age Note how easy it is to access any field of a JSON object, which is definitely not compared to accessing specific information in the PDF document. How does JSON differ from PDF? Although PDF and JSON are both widely spread and used, there is a huge difference between PDF and JSON. The difference between them is simply in the purpose of their usage. PDF is mainly used for exchanging information between humans, since it contains text, graphics, illustrations such as images and videos, etc. On the other hand, JSON is mainly used between computer programs and different applications for communicating and exchanging data between each other. It is not an easy task for a human to read information from a JSON file, especially if it is a compressed one, but it is a perfect way to access information from JSON for a software application. The opposite goes for the PDF. Therefore, PDF and JSON become important, useful, and helpful only when they are used in the right place and for the right purpose. How to Convert PDF to JSON? Often, organizations need to transfer data to other programs for further processing. This data is often stored in PDF documents since businesses often speak to each other in a “PDF language”. However, extracting information from PDF documents can be challenging.  The simplest solution is that you can always copy and paste text from a PDF and send it to where it belongs. However, this simple approach has many problems, since first of all this will work only with native PDF files (not scans) for which you can even use some free PDF Parsers. Another problem even if your PDF documents are all native, it is not easy to copy the entire table from a PDF by maintaining its format, especially if the table spans over multiple pages, for example, 100 or 1000 pages. Additionally, often organizations need to extract specific data from PDFs, for example not the entire table, but instead specific rows or columns based on some conditions. Last, but not least, it is not worth spending your valuable time on menial data entry! Convert PDF documents to JSON with Algodocs Algodocs offers a perfect solution to extract any type of data from PDF documents and transfer it to other programs in real-time. Algodocs can extract fields and tables of any complexity from native as well as scanned PDF documents. You can convert your PDF documents to JSON in three steps with Algodocs. First, start by creating an extractor in Algodocs. Algodocs has some preprocessing operations that take some time depending on the number of pages your PDF document contains; usually, it is around 15-20 seconds. Then, go to the ‘Extracting Rules’ editor to create your extracting rules for every field you need to extract from your PDF documents. Similarly, if you need to extract tables from your PDF documents you can create extracting rules for tables by selecting ‘Table’ as the data type. After you are done with creating and extracting rules,

Algodocs

Extract handwritten text from scanned PDFs and images

Back to Blog Table of contents On this page Extract handwritten text from scanned PDFs and images Home › Blog › Algodocs › Extract handwritten text from scanned PDFs and images Categories Algodocs Tags ai platform for data extraction algodocs character recognition data extraction from images deep learning export extracted data to excel invoice process machine learning ocr api web-based ai platform for data extraction By Shubhankar Biswas Published October 13, 2025, 11:56 Updated November 10, 2025, 13:34 Optical Character Recognition (OCR) engines are primarily focused on machine-printed text and may produce low accuracy for handwritten text. Intelligent Character Recognition (ICR) is an advanced recognition system that is used to recognize handwritten text. This allows the automatic conversion of text in an image into letter codes that are usable within computer and text-processing applications. Although many processes involve computer-based operations and are implemented in a digital environment, paper is still vastly used across most core business processes such as mortgage origination, order fulfillment, contracts, and other documents that usually require handwritten input and signatures. Nowadays, the digitalization of paper documents plays an important role, and deciding on the right data capture software is critical since handwriting recognition unlike printed text recognition is a more complex task that usually involves advanced deep learning algorithms. Algodocs: Deep Learning Handwriting Recognizer Algodocs is capable of converting handwritten text into machine-printed text with high accuracy. With the ICR of Algodocs, you can automate your document processing workflow and get rid of manual data entry. Scan your paper documents with handwritten text and let Algodocs automatically extract data and convert it to Excel or JSON. Let’s consider the following portion of a scanned document, which contains a table of two columns filled with handwritten numbers. If you upload this image to your account at Algodocs, you will see the following output, which has 100% accuracy. Algodocs uses advanced ICR engines trained with Artificial Intelligence algorithms and Deep Learning. The above example includes mostly digits. Another example with characters is given below. The following is the extracted text by Algodocs from the above image. As we can see Algodocs performs well in handwritten text extraction from scanned documents. Feel free to start a free subscription right now and test your handwritten scanned documents. You can use Algodocs free forever with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. If you have specific requirements and need a custom solution, please contact us. You Might Also Like How to Extract Handwritten Data from PDFs with Algodocs? Table of Contents Want to learn how to extract handwritten data from PDFs easily for your business documents? Algodocs is a powerful AI platform… Shubhankar Biswas October 13, 2025 Conquer Multilingual Data Extraction: A Step-by-Step Guide with Algodocs Introduction Sick of spending hours manually extracting data from multilingual PDFs and images? It could be more efficient, prone to mistakes, and,… Shubhankar Biswas October 12, 2025 Why convert PDF to Word on MacBook (Mac)? Picture this: You have a PDF file that needs to be revised or a scanned document that you wish to convert into an editable format like an MS Word… Shubhankar Biswas October 12, 2025 Start extracting your data today No credit card required. Process up to 50 pages per month on the Forever Free plan. Book a Demo Get Started for Free

Image Data Extraction

A Guide on Extracting Tables From Low-Quality Scanned Documents

Back to Blog Table of contents On this page A Guide on Extracting Tables From Low-Quality Scanned Documents Home › Blog › Image Data Extraction › A Guide on Extracting Tables From Low-Quality Scanned Documents Categories Image Data Extraction Tags ai platform for data extraction algodocs character recognition data extraction from images deep learning export extracted data to excel invoice process machine learning ocr api web-based ai platform for data extraction By Shubhankar Biswas Published October 13, 2025, 11:52 Updated July 22, 2026, 09:54 Many companies deal with thousands of documents every month. Document workflow automation becomes vital for such companies as the number of documents increases. One of the most frequent and at the same time tedious operations when processing documents is reading data from tables, especially when documents are scanned PDFs or images. Automating table extraction from scanned documents and exporting them into Excel or JSON within seconds is a dream for every company dealing with manual data entry. Automating table data extraction from scanned documents and images reduces operational costs and saves a lot of time. In this article, we will talk about table extraction from scanned documents or images with low quality. You, most probably, came across some online tools that can extract tabular data from documents. However, there are a few that really work with low-quality scanned documents or images taken by a mobile device. Optical Character Recognition (OCR) is the technology used for converting scanned images into text. However, standard OCR tools require you to apply certain image processing operations on the images before you can apply OCR on them. Without manual pre-processing, OCR will fail in most cases, and accuracy will be low. Unfortunately, even with pre-processing operations free OCR tools produce poor performance. How to extract tables from scanned PDFs and images with low quality? Algodocs has an advanced AI-powered OCR engine that automatically handles any type of scanned PDF or image with a low quality. Algodocs accepts either colorful scanned images, black and white, or any other settings and extracts data with high accuracy. Algodocs can process scanned images with as low a dpi as 75. If you have scanned PDFs or images with low quality, then Algodocs is the right solution for you. You may start a free subscription right now and test your own scanned documents since we offer a free subscription (forever) with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. Please read our article on the basic steps for table extraction from documents here: Extract tables from PDF and scanned documents Algodocs: the best software tool to extract tables from scanned PDFs and images Consider the portions of the scanned documents below and the tables that Algodocs extracted from them. Example #1 Sample scanned image with low-quality (black and white) Extracted table by Algodocs. Example #2 Extracted table by Algodocs As you can see, the accuracy of Algodocs is perfect even with low-quality scans. However, there are cases when scanned images may cause Algodocs to make mistakes concerning small characters such as punctuation or other symbols (points, commas, date separators, etc.). Let’s have a look at the example below with a scanned image and see what Algodocs could extract from it. The extracted table from the above-scanned image is shown below. As you can see, there are numbers that are extracted with wrong decimal separators (indicated in red circles), i.e. a decimal point is mistakenly recognized as a comma. This is due to the dark background that some rows have on the image. With the help of flexible extracting rules of Algodocs, the workaround is quick and simple. Whenever you have low-quality scanned PDFs of images, we always advise you to follow the steps explained below. Step1. Remove all points and commas from the numbers We apply the ‘Search & Replace’ filter in Algodocs by using regular expressions as the search type. We apply this rule to all the columns in the example below, but you can restrict this rule to a specific column when needed. In order to find all dots or commas we use .|, as the search term and we leave empty the second field (replace by this), since we simply want to remove them. Step 2. Convert all numbers to their previous format Since we removed all points and commas from numbers, they actually increased, i.e. multiplied by 100 we can say (2,378.63 became 237863). Therefore, since we know that our numbers had 2 decimal places, we can divide all numbers by 100 to get the original numbers. The ‘Arithmetic Operation’ filter helps us implement exactly this. We divide numbers by 100 in the last column as shown in the example below. You may apply this filter to other columns too. That’s it. We got numbers in their original form with 100% accuracy! The same approach can be applied to other symbols when you have documents with a low quality. Please, contact us if you need any assistance. You Might Also Like How to Extract Handwritten Data from PDFs with Algodocs? Table of Contents Want to learn how to extract handwritten data from PDFs easily for your business documents? Algodocs is a powerful AI platform… Shubhankar Biswas October 13, 2025 Data Extraction for Legal Industry : How Intelligent Document Processing (IDP) Can Transform Legal Industry Document Workflow The global law and legal services industry is expected to reach $1,591.56 billion by the end of 2032, according to a report. The legal industry… Shubhankar Biswas October 12, 2025 Extract Tables from Images with AlgoDocs Extract Tables from Images with AlgoDocs One might find themselves overwhelmed by a deluge of paperwork—orders, checks, articles—all containing… Ibrahim Nalbant June 20, 2024 Start extracting your data today No credit card required. Process up to 50 pages per month on the Forever Free plan. Book a Demo Get Started for Free

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