AI Document Classification: Real Estate Example

In the fast-paced realm of real estate, navigating through stacks of paperwork—property listings, contracts, inspection reports—can seem like an endless task. And when you’re on the hunt for that vital piece of information? It’s almost like searching for a needle in a haystack.

This is where automated document classification comes in handy – usually a system or a tool that sorts and organizes all your documents automatically, ensuring everything is neatly indexed and easy to retrieve. No more endless searching, no more misplaced files. Just instant access to the information you need, when you need it.

What is AI document classification?

AI document classification or document categorization implies assigning categories, labels, or tags to the document based on its layout, text and visual content, and general appearance to facilitate document analysis, management, and storage. Document categorization is the first step of a broader process called Intelligent Data Processing (IDP).

AI document classification is beneficial for paper-heavy industries like finance, healthcare, and real estate, automating time-consuming repetitive process of manual categorization. For example, property managers drown in a sea of lease agreements, maintenance requests, and tenant complaints. Meanwhile, real estate agencies deal with a constant influx of property listings, buyer inquiries, and legal contracts.

Among others, AI document classification can help real estate companies and professionals with residential loan applications, appraisal reports, financial statements, lease agreements, property management documents, sale contracts, and mortgage documents.

How does AI document classification work?

AI document classification relies on Natural Language Processing, Machine Learning, Deep Learning, Optical Character Recognition, and Computer Vision. It takes three steps: identification of file format, document structure, and document type.

Document Submission:

The user submits documents through various channels customized for their workflow. This could include:

• Uploading documents directly through a web-based application interface tailored to their organization’s branding and requirements.
• Integration with existing document management systems or cloud storage platforms, allowing seamless transfer of documents.
• Email integration, where users can forward emails with attachments directly to a designated email address linked to the document classification system.

Document Classification:

• File format identification.
  PNG, PDF, XLS etc.
• Identifying the document structure.
  Contacts, invoices, application forms, and other documents have different structures with distinguishing elements. AI identifies those specific features and categorizes documents according to them.
• Identifying the document type.
  Unstructured, semi-structured, or documents that have similar layouts have to undergo final document categorization after text analysis. AI looks for key phrases or specific terminology to attribute the document to the relevant category. For example, the key phrase “Closing Statement” is a part of contacts, not invoices.

Results Presentation:

Once the classification process is complete, the system presents the results to the user. This could be in the form of a categorized list of documents, with each document assigned to its respective class or category.

Some tools also offer document abstraction features, particularly useful if you want to avoid sifting through lengthy documents. For instance, if your lease spans 20 pages, the system can swiftly provide you with a lease abstract. This applies to various real estate documents like invoices, appraisal reports, and contracts.

At AscendixTech, we’ve developed an AI abstraction and classification tool that not only organizes documents efficiently but also provides summaries and key information. With our solution, you’ll never have to spend time digging through lengthy documents again.

Structured vs Unstructured Documents

Some documents can be structured, unstructured, or semi-structured and it hinders document categorization. For example, application forms are structured documents – they have a standard layout and only data in the fields vary. Such documents are more amenable to AI document classification. Meanwhile, contracts, the best examples of unstructured documents, are the most difficult to classify based on solely appearance.

AI Document Text Classification

The first step in AI document text classification is to extract the text from the image or scanned document. Optical Character Recognition is the technology that is responsible for extracting text from images or scanned documents, recognizing and converting handwritten text into editable digital ones.

After text recognition, Natural Language Processing is responsible for further document analysis using extracted data. NLP understands human language, content, context, and the semantics of the text, which is crucial for AI document analysis of unstructured files.

For example, NLP algorithms can be used to identify key concepts, entities, and relationships within the text, and to extract relevant information such as key terms and conditions in contracts, such as purchase price, closing date, and contingencies from unstructured contracts and this way correctly classify it to the relevant category.

Visual AI Document Classification

Visual AI Document Classification means that during AI document analysis, the system considers only images, diagrams, and other visuals without analyzing the text.

Some documents in real estate can contain visuals that can’t be processed by OCR, so Computer Vision and Object Detection are implemented. Those two technologies focus on recognizing images pixel-by-pixel. AI classifies and sorts a bunch of photos of different properties by similar objects instead of real estate agents. Restb.ai is a good example AI solution in real estate that leverages Object Detection. Object Detection recognizes QR codes and bar codes on checks provided by repairmen after maintenance, so property management doesn’t have to sort them into the right folder. Those are only two examples of how AI benefits real estate professionals.

Methods of AI Document Classification

There are three methods of AI document classification: supervised, unsupervised, and semi-supervised. Neither of them is related to human supervision, everything is automated.

Supervised AI Document Classification Using Machine Learning

Supervised AI document classification is one of the most precise, but also the most difficult to implement. You need to feed a database with already labeled documents to train the model. document classification AI will automatically categorize the documents based on those data. The higher the quality database, the more precise document categorization because the system will know what to focus on. AI looks for key phrases or specific terminology to attribute the document to the relevant category. For example, the key phrase “Closing Statement” is a part of contacts, not invoices.

For final document categorization, Machine Learning gets involved to enable computers to learn from data and make predictions or decisions. ML is used in document classification to train algorithms to assign labels or categories to documents based on their content.

Unsupervised AI Document Classification

Unsupervised AI document classification relies on deep learning to train a neural network to identify patterns and relationships in a large dataset of documents, without the need for labeled examples.

This way, the document classification AI makes decisions based on the differences between documents, not similarities with given examples as in the supervised method. The disadvantage of unsupervised AI document classification is lower accuracy. AI learns to identify patterns and relationships within the documents themselves.

Semi-supervised AI Document Classification

Semi-supervised AI document classification in a combination of supervised and unsupervised methods using both a labeled training dataset and unlabeled data.

Benefits and Challenges of AI Document Classification in the Real Estate Industry

As with any technology, AI document classification brings many benefits to paper-heavy industries, especially real estate. However, there is always a set of challenges to overcome.

Similar But Different Real Estate Documents

Some documents in the real estate industry have similar layouts and text, so they might look the same for document classification AI. For example, the Property Disclosure Statement and Home Inspection Checklist are two different documents, but their layout and text are very similar.

Both consist of tables and checkboxes and contain the names of parts of the house. When using only unsupervised and visual document classification methods, the AI document classifier might group them into one category. Meanwhile, supervised AI document classification using machine learning recognizes the slightest differences and categorizes documents with the highest accuracy.

Of course, each document has a title, so the document classification AI can rely on the title and there is no problem. In fact, there are some. A document’s title doesn’t always provide enough context to accurately classify it. For example, a document titled “Home Inspection Report” could be a report on a home inspection for a real estate transaction, or it could be a report on a home inspection for a homeowner’s insurance policy. Different documents, but after AI document classification that is not supported by ML and examples from database, they happened to fall into one category. The same goes for appendixes that have titles similar to other documents.

The worst-case scenario is when one of the documents gets deleted by the document classification AI as a double. Since real estate professionals and companies deal with a huge influx of different documents, sometimes some of them get uploaded multiple times. When it’s updated, the system automatically replaces the file with a more up-to-date copy. Unfortunately, when similar documents are uploaded together, one of them usually gets deleted. When the system is not advanced enough, such situations are inevitable.

To avoid the above cases, the best approach is to use a supervised AI document categorization method with a labeled database to eliminate possible errors. The simpler method is to implement notifications that will ask the user for permission to replace or delete the document, but it will limit automation due to the requirement of manual checking.

Regulatory Compliance and Fraud Detection

Detection of anomalies is a core of AI document categorization: the system analyzes the document, identifies the features that are implicit for the specific type of document, and sorts it into the relevant category. This process can be used for fraud detection. Slight differences in the layout, defunct address, unreal property characteristics, and much more can be detected by document classification AI and prevented from further processing.

Also, detecting inconsistencies in real estate documents can be useful when it comes to regulatory compliance. For example, real estate documents, such as purchase agreements, sale contracts, and deeds, are typically governed by state law, and each state has its own specific requirements and regulations regarding the content and format of these documents. With document categorization AI powered by specifically labeled databases, real estate companies and professionals can be sure that all their documents are legitimate. Also, document classification AI can detect empty fields that must be filled, it can return the document for revision.

Bulk AI Document Classification

The number of documents in real estate is overwhelming. But when document categorization AI can’t perform a few files simultaneously and requires uploading them one by one, the automation does not bring the desired process facilitation. That’s why it’s best to opt for document classification tools that allow for bulk file uploading to categorize all necessary documents in one go.

Integration With Email, Cloud Storage, and CRM

Most of the documents are sent by email, but not all systems support integration with inbox, so the user has to download all the attachments one by one and after that upload them to the system. That’s why, directly connected to the inbox or cloud storage document classification AI automatically categorizes documents without user participation. Also, documents and data usually should be added to the CRM system or company software while AI data entry helps to update necessary fields automatically.

AI Data Entry Tool by Ascendix

Data Protection

Real estate documents contain a lot of sensitive and personal information. After massive hacker attacks and data leaks, many countries impose strict requirements on the processing and storage of personal data, and failure to comply can result in significant fines and penalties, and loss of reputation in the eyes of clients. Unlike generally available online solutions, tailored AI document classifiers can guarantee advanced encryption and robust data protection.

Top 3 Document Classification AI Tools

Google Document AI

Google’s Document AI is a comprehensive solution for document processing. This platform allows businesses to automate document classification and data extraction tasks, streamlining document workflows.

The main competitive advantage of Google Document AI is that this service can handle unstructured documents. It utilizes advanced machine learning models to automate the process of extracting data, classifying documents, and splitting multipage documents into smaller, more manageable parts. Also, Google Document AI can be connected to all services of Google, including Gmail inbox, which is extremely convenient.

However, a lack of specialization in real estate can lead to the misclassification of some documents, especially complex forms. Also, Google Document AI can’t do batch processing while real estate workflows often involve processing large amounts of documents simultaneously.

Docsumo

Docsumo is an intelligent document processing platform that uses AI and machine learning to automate data extraction from unstructured documents like invoices, contracts, and receipts. The validation process involves a human review to add reliability and accuracy. Except for traditional features of document classification AI, Docsumo also includes additional functionality, like the possibility to convert documents into different formats, split, merge, and compress files within the platform. Also, It allows bulk AI document processing and has solutions for the real estate industry. Unfortunately, Docsumo struggles with specialized and unstructured documents as well as handwritten text.

Artificio

Artificio is a new AI solution that offers AI document classification for many industries, including real estate. The service provided by Artificio includes features like AI OCR and document classification, NER for extracting key pairs, table line-items extraction, data verification, validation, and anomaly detection, as well as integration with property management systems and databases.

Artifio Interface | Artificio

Artificio is tuned for the real estate industry and even has a few client feedbacks on the website. However, It has no reviews on reputable websites, so it’s difficult to estimate its reliability. Also, Articio is surely not the cheapest solution with subscription plans of around 599 USD.

Ascendix Expertise with AI Tools Development

Ascendix has deep knowledge of modern technology, practical experience with custom AI tools development, and 16+ years of expertise in real estate. With more than two decades of experience in custom dev, we have developed software solutions for big enterprises like JLL as well as small startups, delivering high-quality and tailored tools for various industries.

We have built custom AI software for document classification, AI search, lease abstraction tools, AI recommendations, and other advanced software and have successfully launched 17 of own products.

How Can Ascendix Help You with AI Document Classification?

• Custom AI Document Classification Tool Development. We have created a robust framework with a specifically trained model that can be tailored to your business needs.
• Integration of existing or custom solutions. If you have an existing solution in mind, that you would like to integrate into your software, we can do this for you, developing and optimizing all the features and customizing the solution for you.
• Machine Learning Model Training. Leverage supervised document classification with machine learning capabilities for the most accurate results.
• AI Implementation Consulting and Strategy. We can help you choose the most suitable AI solution, suitable for your business needs.

Schedule a free consultation to find out how AI document classification can streamline your business processes.