Modern companies have to process vast quantities of invoices, letters and other documents. The problem: senders do not adhere to uniform rules in any way. Central information such as invoice or transaction numbers is always in a different place. This makes the Document classification to a Sisyphean task. The solution: "AI Data Extraction" - data extraction with modern AI.

What is AI Data Extraction?  

This type of data extraction is not to be confused with a so-called data lake, which is merely the prerequisite for the use of AI. AI Data Extraction goes beyond the mere schematic collection of data. In doing so, AI performs superhuman tasks. It is adaptive, Structures the raw data and meets accurate predictions for the optimization of processes. For companies, this service means real added value, as AI increases data quality and reduces costs.

With AI Data Extraction, employees can save themselves the trouble of manually entering or copying data from documents in the future. AI will do it for them. In addition, data extraction software minimizes the risk of human errors during data entry in a digital world.

AI is more flexible than rule-based data extraction software

Before the use of AI, data extraction processes were template-centric. This meant that employees had to create a template for each group of documents with a similar structure. Companies must manually configure such an input management system. Agents specify how they want to transfer numbers and data from documents into target systems by following certain rules.

But that quickly reaches its limits with today's data volumes. Companies must daily process hundreds of pages and deal with many different document classes. The consequences: Precision and recognition rate decline. The system functions less and less automatically. The effort required for system maintenance and post-processing increases. The only solution is to switch to processes with Machine Learning: Data extrusion software must become intelligent.

Data extraction tools help with automation

Data extraction with AI goes beyond standard functions such as optical text recognition (OCR) by far. In addition, there is a Natural language understanding, Natural Language Processing (NLP). This enables an API (Application Programming Interface) to correctly understand, evaluate and assign data. AI algorithms are used, which can read texts and similar to a human brain be able to interpret.

However, humans must first configure such a platform for customer requirements. The AI has to be "learned", so to speak. The AI learns through a wealth of training data and defined rules. Employees make corrections in the process so that the machine applies the rules better and better. To prevent performance from dropping, powerful AIs even manage to learn from their own mistakes and thus become always smarter.

The secret of this wonder weapon is called "machine learning". The AI uses the clerks' corrections to improve itself through unsupervised learning. Employees can sit back and watch as the AI learns, but is still oriented toward humans.

What are the benefits of AI Data Extraction?

To keep up in the market, companies are increasingly relying on systems with AI. Classic automated processes with OCR and ICR (Intelligent Character Recognition) are no longer sufficient to Competitive advantage to work out. Data Extraction has several advantages:

• better data quality
• Reduce costs
• Implement processes faster
• Automation of data entry

Why is data extraction with AI important for businesses?

On average, 20 % of a typical digital company's database is full of unorganized data. Such "dirty data" impairs business success. AI Data Extraction reduces errors, Brings order into the data and leads to more accurate results.

Time is money: When team members Less errors have to correct when extracting data, it saves a lot of time. Instead, they can focus on other tasks, which increases revenue. Important decisions can be made much more efficiently through data extraction with AI, as employees no longer have to search for the necessary information themselves.

Modern data extraction software organizes documents easily

Software tools that capture unstructured data and make it machine-readable are important for data extraction. First, the AI software the document at different data points. This creates Structured digital data, which tell the system where to look in the documents. Now the system knows what kind of data the company wants to extract. The automatic data extraction can begin.

After the extraction of the data has begun, the AI can use the Automate process. To do this, the API must collect enough documents and, using machine learning Learn intelligentlyhow to extract the data. Humans hardly need to check this process.

Team members can then easily forward the organized documents, resulting in faster business decisions leads. This puts an end to the eternal search for data. The data extraction process can be fully tailored to individual business requirements.

Modern Data extraction software is even able to work efficiently with different languages to handle. To do this, the human must show the machine sample documents in that language. When the computer understands the content of documents, it can also recognize contextual nuances of the corresponding language. This technology can thus categorize and organize information in documents much better.

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