Tired of manual data entry? AI-enabled data extraction is here

Are you tired of spending your time manually sifting through emails and filling in forms for employee onboarding, invoice processing, insurance policies, and other critical service tasks?

Well, your prayers have been answered because we’ve built an AI-enabled solution that can automatically extract data from emails and auto-populate forms. Our progressive solution slashes the time spent on monotonous tasks such as data entry, and gives you more bandwidth to spend on value-added work.

What is data extraction?

Data extraction is simply the act of retrieving specific information from a source, for example, a document, email, or database. This data is then ready to be used for whatever purpose you need, like analysis, reports, or entry into any manner of form. Once upon a time, extraction was a task that took hours of tedious data entry and cross-checking, but AI has arrived to revamp the whole procedure.

How does AI data extraction actually work?

AI data extraction or entity recognition works by using Natural Language Understanding patterns to recognise key ‘features’ or entities within a block of text. For example, an email. Typically data extraction is conducted with the use of a large trained model and has been great for finding things like: proper names, locations, dates and times etc, but has been less accurate when locating more domain specific terms and entities. For instance, within a medical or legal email there may be certain domain specific entities you want to understand, but the implemented model is too general. This is where EnateAI steps in, implementing LLMs (Large Language Models) alongside our workflow orchestration platforms means that we are able to quickly map entities within your data to the Enate platform, saving critical human time reading and processing email.

Example use case: Processing claims in the insurance industry and being able to extract the claimants name, their claim number and the content of the claim directly from a submission enables their claim to be processed faster.

The benefits of AI-enabled data extraction

Any business dealing with large volumes of emails, service requests, invoices, and other documents stands to benefit from EnateAI. Our AI-enabled solution intelligently scans forms and text, extracting relevant data, and processing it as required.

• Reduction in manual work
• Heightened efficiency
• Improved accuracy
• Reduced risk of human error
• Streamlined workflows
• More time to focus on customer success

AI data extraction applications across industries

Finance and banking

This is an area where accuracy is vital and mistakes cause major headaches. AI data extraction alleviates this stress, able to quickly pick out the necessary information from receipts, invoices, loan applications, financial statements, and any other financial paperwork, in a fraction of the time and with minimal errors.

Healthcare and pharmaceuticals

Healthcare providers must be able to access patient data quickly and easily to deliver a high standard of care. By automating data extraction from medical records and other forms, this information is readily available to them. Plus the reduction in administrative work gives healthcare workers more time to focus on patient care.

Retail and e-commerce

One of the most important aspects of retail and e-commerce businesses is customer experience, and a big part of that experience is the speed and efficiency of the service they receive. Manually managing purchase orders, inquiries, and inventory management can slow everything down. AI data extraction, however, expedites every step, preventing delays and costly mistakes, which in turn means happier customers.

Legal and compliance

Between legal documents, regulatory filings, contracts, and a host of other paperwork, legal and compliance is an area that gains huge time savings from automated AI data extraction. Less time spent on manual review and a lower risk of errors means compliance and legal standards are met without the usual hassle.

Historically, entity and feature extraction hasn’t cut the mustard

To date, entity or feature recognition has been constrained by the data available for training the underlying model. Typically, these models have been owned by large cloud platform providers and offered as a general service to consumers. Whilst this meant that the traditional cost of a lengthy machine learning (MLOps) pipeline had been removed (collecting data, cleaning data,  training, testing etc), the models have often been highly general. Previously, challenges arose in accurately identifying specific domain language and entities, resulting in variable accuracy. This often prolonged development cycles for consuming services or lengthy projects that might not lead to entity recognition adoption.

Best practices for implementing AI data extraction

Select which tasks to automate

To start, you need to identify those processes where you want to automate data extraction. It’s a good idea to begin with a high-volume task that will have big efficiency rewards, such as invoices or customer emails. Knowing your objectives will help guide you in the next steps.

Choose the right AI data extraction tool

Look for a model that is scalable and will tailor to your industry and the specific needs of your business. A generic model can handle common data types, but for domain specificity, you need a tool that is integrated with LLMs and able to handle specialised data, like legal documents or medical records. These models can perform to a high degree of accuracy across sectors.

Integrate with existing systems

Uninterrupted data flow is vital for data extraction, so you need a tool that will integrate with your current platforms, like your document management system or CRM. Manual intervention is then minimised and automation will do all the work for you, allowing the extraction tool to bring the maximum benefit.

Conduct pilot testing

Before you launch full steam ahead, test a small sample dataset to assess how the AI model performs and establish if there are any issues that need to be addressed. A good model should be working to a high degree of accuracy right out of the gate, but this gives you the opportunity to make any necessary changes to fix inaccuracies or other problems.

Provide training for your team

The right tool should be accessible and easy to use for everyone, but it’s still important to provide sufficient training so that your team feels confident using the new AI system. Training should give them an understanding of how it works, how they can use it for specific tasks, and how to troubleshoot any problems.

The future of AI data extraction

The automation of data extraction is undoubtedly here to stay, but there are other innovations set to shake things up even more. Enhanced Natural Language Processing (NLP) has introduced the ability for AI systems to comprehend the context and nuance of the extracted data, further improving accuracy – especially for more complex data like customer emails.

AI data extraction models will also evolve to include decision-making capabilities, interpreting data and suggesting next actions, further speeding up various tasks. Another area likely to develop quickly is ethical and responsible AI practices. Steps will be taken to address biases and further strengthen data privacy as these tools become more widespread, alleviating current hesitancy around AI and keeping pace with cyber security threats.

EnateAI for data extraction

With EnateAI's integration with LLMs, powered by extensive data trained across diverse domains and industry-specific language, the need to repeatedly enhance or expand services for new feature extraction is eliminated. Trained on extensive datasets across diverse domains such as legal, medical, and insurance, LLMs possess the capability to comprehend various natural expressions. EnateAI automates the process, seamlessly aligning with your defined data in the Enate platform.

EnateAI - 5 AI features in one

Email data extraction is just one of 5 fantastic EnateAI features. EnateAI has been specifically built to elevate operational efficiency and can effortlessly categorize emails, perform sentiment analysis, comprehend foreign languages and automate queries.

Embrace a smarter and more effective way of working, empowering your service team to achieve more in less time, and ultimately, enhancing overall customer satisfaction. To see for yourself what Enate AI can do for your business, book a demo today.