Power Up Document Classification with Machine Learning
Automatic document classification leverages AI technologies to automatically recognize and categorize documents, making them easier to manage, search, and processed.
If you're trying to reduce data entry and start automating your processes, Machine Learning & OCR might just be what you need!
Automating your business doesn't mean you'll be replaced by a robot. Rather, it means you'll have the tools to make yourself more efficient and free up time for other tasks. If you're trying to reduce data entry and start automating your processes, Machine Learning & OCR might just be what you need!
This post will give an overview of how machine learning can help automate tedious data entry tasks so that employees can focus on higher-value work. We will also go over how Optical Character Recognition (OCR) works and some examples of companies who successfully use these technologies in their workflow today. By the end, we hope that you'll see how using these automation tools could benefit your business as well!
Data entry automation is a software-based solution for optimizing any data that's being input by eliminating or reducing manual processes. It can be used to extract information from PDFs, documents, images, and emails to make it easier for the user.
The data that's being input may be part of a new customer onboarding process, updating an existing customer's information, processing invoices or purchase orders, etc. Anytime you have to request information from someone else and type it into your system is an opportunity for automation.
There are several types of software available for automating data entry, depending on why you need the automation to take place. In this post, we'll focus on Optical Character Recognition (OCR) and Machine Learning – both of which play a critical role in automating data entry tasks.
Machine learning is a field within artificial intelligence that allows for systems to become more accurate with the prediction the longer they are used. The goal of machine learning is to allow computers to learn on their own from data without being programmed specifically how to do so. There are two main types of machine learning: supervised and unsupervised.
Supervised: In supervised learning, an algorithm will receive inputs and expected outcomes. By using training data that has properly tagged inputs and desired outcomes, the algorithm learns how to map new inputs to desired outputs by adjusting its weights based on error correction until it is accurate enough. Once computing power became more accessible, this method of machine learning grew in popularity. Unsupervised: In unsupervised learning, no expected outcome is known. The system is therefore trained using unlabeled data. The algorithms self-discover patterns within the data and can categorize inputs based on those patterns.
Machine learning is used in virtually every industry today to process large amounts of data, find useful insights, and make predictions. For example, many businesses use machine learning to predict things like customer churn, stock market traders, and credit card fraud – just to name a few.
One of the most common use cases for machine learning technology is in improving data capture processes. Machine learning algorithms can be fed a dataset of inputs and expected outcomes to find patterns. Once the algorithm finds those patterns, it will begin making predictions on new input.
In practice, data capturing software like FormX utilize machine learning algorithms to improve the extraction results. For example the computer can learn how to correct the misaligned or poorly lit images so the successful rate of extraction from user-scanned images can be increased. The algorithms can also learn from the semantic and layout patterns from the labeled samples. Such that, when a document of unseen format is processed by the extractor, the algorithm can make predictions and extract the right data from the correct location based on previous training.
Automated data entry is a process that can be used by companies of any size, and it has many benefits for both businesses and their customers. The use of automated data entry can increase the speed at which information gets into the system as well as reduce errors within the company's database.
Once a company has implemented automated data entry, they have streamlined the way that information gets into their system. The process allows them to save time and money on things such as updating a customer's address or demographic information, which will ultimately improve the overall experience for their customers. With automated data entry, companies can reduce the costs of hiring employees who are tasked with these types of tasks. They also have the advantage of being able to handle a larger volume of information in less time.
This also helps eliminate errors and will ultimately save time in the long run. It can also be used in conjunction with a robotic process automation tool to improve the accuracy of all data entry processes.
When companies can use automated data entry to improve their process, this will ultimately contribute to the company's bottom line. The faster that information can get into a system, the faster that it can be processed, which then leads to more revenue for the business. Ultimately, data is money, and by implementing an automated data entry process, businesses can increase their overall efficiency and get more out of every sale.
FormX is an OCR API that you can use to automate data entry, which takes data from connected devices and puts it into a business' existing systems. It can be used to update customer information, as well as automate certain processes such as billing and inventory management. The technology uses automated data entry for individuals who input orders or process transactions through the use of forms. This allows businesses to save time and money on data entry.
The future is here, and machine learning will play a major role in the way we handle big data and make sense of the world around us. Machine learning and automation has already become the go-to solution for businesses looking to handle large datasets or take advantage of opportunities where human intervention isn't feasible. Every day, machine learning is expanding into new industries and solving problems that were once thought to be impossible.
Businesses can find a competitive advantage by understanding and utilizing the power of machine learning technology and automation to increase productivity and better serve their clients. Interested in learning how your business can take advantage of this technology? Contact us with any questions or suggestions, we would love to hear from you!
For any additional questions on how your business can utilize machine learning technology, contact us on this page.