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What is Cloud-Based Data Extraction? [A Guide]

Miranda Hartley
July 2, 2024

Data Extraction: A Definition

Data extraction is the process of identifying and retrieving the requisite information from a source (e.g. a PDF, image or webpage). A simple example of data extraction might include copying data from a balance sheet (PDF) into a spreadsheet. 

Data extraction falls under the category of back office or administrative tasks. Clients looking for an automated and cloud-based data extraction solution generally want to eliminate manual data extraction from their day-to-day work. Manual data extraction is tedious and time-consuming – and, nowadays, obsolete. 

Originally, automated data extraction technologies required time-consuming on-premise installation. However, the rise of cloud-based data extraction platforms has made deploying these technologies faster and more user-friendly.

Accounting For the Rise of Cloud-Based Data Extraction

Cloud-based technology refers to technical services available via an internet connection. Instead of buying and operating data centres, cloud users can access a vendor’s technology on demand.

According to the Chartered Institute of IT, the ubiquity of internet access, combined with the collaborative features cloud computing offers in an increasingly remote and global job market, means that cloud computing isn’t exclusively for companies with deep pockets.

Cloud-based data extraction has arguably democratised access to data extraction services. Previously, only companies that could afford expensive on-premise installation and maintenance could experience the benefits of automated data extraction. Now, companies can use cloud-based SaaS data extraction solutions more casually. For example, an accountant might use a cloud-based solution to extract data from a handful of bank statements on an ad-hoc basis.

Applications of Cloud-Based Data Extraction - Financial Services

Manually processing financial documents – with their lengthy lifecycles and multiple touchpoints – is a major pain point for companies in the financial services sector. Many organisations are turning to cloud-based data extraction technology to streamline this process.

Take an invoice, for example. A vendor’s sales or accounting teams generally draft an invoice and send it to the customer alongside a purchase order. Along the way, a cloud-based data extraction technology will extract data from the invoice, targeting key information like:

  • Invoice number 
  • Date
  • Vendor details
  • Line items (i.e. products and services, prices, etc.) 
  • Total amount. 

Analysts can then use the extracted data for various purposes like payment processing, inventory management and expense reporting.

The use of cloud-based technology makes the flow of invoice data seamless. From customer to analyst, the data is accessible from anywhere while being kept secure.

3 Benefits of Cloud-Based Data Extraction

1. Lower Cost

Cloud computing is generally cheaper than on-premise IT infrastructure. On-premise data extraction hardware requires replacing every few years – costing thousands of dollars for the initial setup each time. The cost of upgrading the servers to maintain competitive performance can also drain thousands from a company’s bottom line.Another cost consideration is that you only pay for what you use with cloud-based data extraction. Whereas, server costs mean that you will always need to account for high levels of network traffic. For example, if you have an influx of documents that need data extracted at the end of the financial year, you may need to purchase and operate a new server that you won’t need (much less use) for the rest of the year.Additionally, running servers involves other costs, such as IT maintenance, electricity costs (including operating and cooling the servers 24/7) and software licenses.When you operate cloud-based data extraction technology effectively, the return on investment (ROI) can be staggering, potentially saving more than 75% of costs.

2. Time Savings

Cloud-based data extraction is easy to deploy — generally only taking a few minutes to get started – once you sign up, you're ready to go. In contrast, a server-based solution will eat up time through configuration and testing. Deploying an on-premise solution can take months if mismanaged, making it crucial for the solution to deliver exceptional results (once operational) to justify the significant time investment.In contrast, because it’s so easy to sign up for a cloud-based solution, it becomes significantly easier to test out or switch between different solutions to find the best fit for your business.Cloud-based data extraction solutions can save companies time in other ways, too. For instance, businesses can scale faster with a cloud-based infrastructure in place. You can expand your services and add-on capabilities without limitations from a physical server.

3. Better Disaster Recovery

Cloud-based solutions can restore lost data from anywhere with an internet connection. In contrast, hardware-based backups often require physical access to the server, which may be difficult when (remote) employees don’t live near the server.Some data extraction vendors can offer automated backup, ensuring your data is backed up regularly without manual intervention. In contrast, hardware backups often require manual configuration, increasing the risk of human error or missed backups.

What are the Limitations of Cloud-Based Data Extraction?

Vendor Lock-in

When a vendor is over-charging and underdelivering, it is still cheaper to stay than to migrate your company to another vendor. In short, you’re locked to that vendor — with no chance of escape.

Working with a data extraction vendor initially involves plenty of back-and-forth about how the data is presented (i.e. data points, format and custom requirements). Moving to another vendor isn’t just a money concern – it also requires patience and organisation to start another relationship.

It’s vital to consider the quality of customer service, but also the vendor’s commitment to consistently improving their technology’s performance through academic and industrial practices. Dedication to innovation is essential for AI-based data extraction vendors. After all, the AI landscape is continuously evolving, meaning that AI-powered data extraction should constantly be getting faster, cheaper and more accurate.


Another disadvantage of being tied to a third-party vendor is that lapses in their system will also affect yours. For time-sensitive tasks like accessing data, downtime may be a source of anxiety. An effective way to check whether a vendor is prone to frequent and extended downtimes is to check their reviews using a third-party platform, such as G2 or Capterra.

Cost Concerns (& Scalability)

Cloud computing has a reputation for being flexible. Its on-demand access model means you can scale your usage as required. However, there may be limits to its scalability.

For example, automated data extraction will become increasingly costly as your business grows and document piles get taller. Let’s say you use a data extraction vendor that charges £0.50p (or $0.50 or €0.50) per document. If you accrue three million pages over the year, you will receive a bill for £1.5 million — an untenable figure for many businesses.

Some businesses may even want to build a custom cloud-based data extraction solution in light of high-volume costs. However, the development costs of building a high-performing data extraction technology will likely be more than simply paying a third-party vendor upfront.

The best way to navigate high-volume costs is to build a relationship with a vendor, enabling you to access and negotiate discounts.

Get Started with Cloud-Based Data Extraction

Evolution AI is proud to present multi-award-winning cloud-based data extraction from financial documents, offering your business:

✔️Complete accuracy

✔️Transparent pricing

✔️Acclaimed customer support

To begin your journey with cloud-based data extraction, please book a demo or email our team at

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