Choosing between template-based and templateless extraction isn’t a matter of technology—it’s a matter of strategy.
At first glance, the choice looks simple: templates offer control and predictability, while templateless systems promise freedom and scale. 

But beneath that surface lies a deeper tension between certainty and adaptability—between systems that follow rules and systems that learn from them.

For many businesses, this decision reflects more than workflow preferences; it mirrors their philosophy toward growth. 

Template-based solutions have been in the market for a long time, but templateless ones are the current hype, growing at a rate of 30.1% CAGR.

In this guide, we’ll move beyond buzzwords and break down how to easily choose between template vs templateless extraction to process your documents.

What is template-based extraction?

Template-based extraction process is a method of extracting relevant information from documents based on predefined templates. The tool locates different data fields using existing document templates as a reference in this method. 

This approach works very well when you’re using documents with a clear-cut template—for example, a PAN card, a bank statement, or a standard invoice format. 

On the other hand, many businesses try to create their own templates and force vendors to adopt them in a bid to standardize. They use template-based extraction for these standardized documents only. But as they onboard more vendors, this process becomes an uphill battle.

Template-based extraction of a standardized document | Source: Zwitch

What is templateless extraction?

Templateless extraction is a flexible and scalable method for extracting information from documents without relying on predefined templates. It moves beyond rigid formats and reads documents using machine learning, deep learning, and natural language processing.

This approach works best when you’re dealing with documents that are tough to box in a format. For example, vendor invoices, bills of lading, and procurement contracts. 

You could start with templates initially. But with scale, it becomes tough to maintain and enforce templates as more and more vendors/suppliers come into the picture. One vendor changes the invoice format, and the entire process breaks. That’s when businesses shift to templateless extraction.

As more businesses are dealing with different document types, they're moving towards templateless extraction.

One of the most prominent examples is Uber.

What are the differences between template-based and templateless extraction?

The choice between template and templateless extraction isn’t just a business decision but also a strategic one. It impacts your operational efficiency.

To help you make an informed decision, we’ve compared key performance indicators (KPIs) that impact your business. 

Accuracy

The concept of template-powered extraction dates back to the 1970s, and more solid research came in the late 1990s. Despite being in practice here for decades, the technology still struggles to meet accuracy standards. The primary reason is the way it functions. 

A vendor changes ‘Invoice amount’ to ‘Total amount' in their invoice structure, breaking the entire system. Accuracy runs on a tight rope of everyone making sure that every party involved doesn’t make any mistakes or changes.

Compared to template-based systems, templateless extraction is way more adaptable. These solutions use Natural Language Processing (NLP) and Computer Vision to interpret and extract data. It doesn’t just scan a document. It actually interprets it to understand context. And then pulls exact information with high accuracy.

Businesses are shifting towards templateless extraction to improve accuracy, create more dependable workflows, and reduce human intervention. 

For instance, a large financial services company was processing a variety of documents. The traditional template-based extraction tools could not handle it. They adopted AI-based extraction, which doesn't rely on any templates, and that shift alone improved overall accuracy and reduced manual effort by ~ 40%.

Templateless extraction of a handwritten invoice using Docxster

Setup time

In a template-based approach, you've got to reach out to developers to design the template and set up the workflow. They'll take their time understanding the document, building templates, and developing/testing the workflow.

It’s a time-consuming setup that can take anywhere from days to weeks. The duration depends on document complexity and the availability of developers.

On the other hand, templateless extraction workflows are often ready in hours. For instance, Docxster just needs the document location and potential field names (not exact names, but something that AI can refer to) you want to pull to create an extraction workflow.

There are minimal configurations. And even those configurations can be done in the user interface by clicking a few buttons. Templateless extractions enable you to create workflows faster, onboard new documents easily, and respond quickly to changes.

Docxster offers a simple console to design any templateless workflow

Labor cost

Template-based extraction is more resource-heavy. You need support from developers to design any new template. The cost varies depending on whether you have full-time developers or take support from freelancers/agencies.

Skilled ML engineers work at an hourly rate of ₹1014.70 per hour. Having even one engineer full-time means a recurring cost of ₹162352.

Taking support from the agency means you’d be paying for the number of hours worked or a fixed package based on the expected time involved. Imagine it took approximately a week and 56 work hours for an automation, then the cost is ₹1014.70*8*7= ₹56823.2 per automation. 

On the other hand, templateless solutions offer a no-code automation interface. Anyone from your team can start creating workflows in a couple of hours.  You need not maintain a separate team for simple workflows. 

Training cost

To adopt a template model, you need to train staff on:

• Developing new document templates
• Creating new document workflows
• Handling changes as new document types roll in

On the flip side, templateless extraction requires minimal to no training. It comes with an intuitive interface that anyone can run from day one. A quick walkthrough of the platform may be enough. Otherwise, the training cost is close to zero.

Simple invoice data extraction workflow built in Docxster by drag-and-drop interface

Processing speed

Template-based optical character recognition (OCR) already knows document layouts by referencing templates. This predictability reduces the processing time. Alternatively, templateless models run complex AI/ML pipelines to understand and break down documents. This complexity increases model run time by a few seconds.

There is also a flip side to it. Template-based extraction models break when any document deviates from the template. And at a large scale, they often do. 

For example, Lawrence Guyot, President, ETTE, a managed IT consultancy, says around 25% of their documents deviate from standard templates. In the event of deviation, manual intervention is necessary to extract the data accurately. 

At the individual document level, a template-based OCR system would run fast for you. But in the larger scheme of things, templateless extraction workflows will handle scale better when your company grows. 

Infrastructure cost

As many template-based extraction solutions often run on-premises, they come with an additional requirement of server costs. It’s costly to maintain servers. 

High-range servers cost upwards of ~₹77,000 per month. On top of it, there are additional costs of electricity, maintenance, and software licenses.

Templateless platforms like Docxster (which runs on the cloud) prove to be way more affordable. You get plans starting at  $45 per month and save on the cost of maintaining internal infrastructure.

Integrations

Template-based solutions provide APIs to integrate with your current tech stack and upload data. You need developer support to configure these APIs in the workflow for integration at work. 

Templateless platforms make it simple with built-in integrations with multiple systems. For example, Docxster provides quick and seamless integrations with popular ERP and CRM. systems. All you need to do is connect your platform of choice through APIs or in-built integrations to activate it. Your data is well and easily integrated into the entire ecosystem with built-in integrations.

Maintenance cost

A major maintenance cost of template-based extraction solutions is having developers on board to handle tweaks in existing documents or add any new documents. 

Jishnu N.P., Docxster’s CTO, says that it’s tough for businesses to maintain a team of developers to handle these changes and additions. The primary reason is that the work is irregular. 

Not every day a new document gets added to the system, nor every day does any existing template break. So, having a dedicated team for it doesn’t make sense economically. It’s also a waste of resources.  

Templateless solutions are low-maintenance cloud solutions. Business teams can make changes if any new field is added to a document or if something is dropped. It eliminates the need to maintain skilled engineers for document handling and processing. 

Flexibility

Template-powered extraction is rigid. Imagine one vendor suddenly changing an invoice field from ‘Invoice Amount’ to ‘Bill Amount’. This tiny change breaks the entire system, putting you at risk of delayed payments and contract clause violations. 

On the other hand, templateless extraction is more fluid and ready to handle different document formats without major pre-handling steps. With templateless workflows, your business is already prepared to onboard a new vendor or process a rare contract. 

Scalability

It’s easy to add any new workflows in a templateless system with simple drag and drop. Also, these solutions often run on subscription models, so scaling means upgrading subscription plans.

In a template-based approach, any change requires developer support. You can build a team of developers or hire a reliable vendor for timely support. There is a heavy dependency on developers to scale, and a time-consuming setup is involved for templates.

Also, if your current computing resources aren’t enough, you need to plan additional CPUs/servers and storage to handle the scale. All these factors make scalability tough in template-based extraction.

Return on investment

The return on investment (ROI) of template-based solutions is initially high for small and static documents. But it drops in the long run, ROI becomes low when considering the cost of:

• Labor cost for handling any document changes
• Labor cost for adding new document workflows
• Infrastructure to run workflows

Templateless solutions have much stronger long-term ROI as they’re easy to start with and easy to maintain, and cloud storage also keeps the cost down.

Security

Typically, businesses have trusted only on-premise template-based solutions. It gave more control over their data and assurance of compliance. But that also means IT teams spend extra time setting up and following security protocols.

Nowadays, even cloud-based templateless solutions are secure, so you don't have to stick with on-premise platforms.

For instance, Docxster is a cloud-based templateless document automation platform. But we’re certified as per GDPR and ISO 27001 standards. So, irrespective of your compliance requirements, you can feel confident while using our platform. Plus, all the compliance standards are built in, reducing the extra work for IT teams.

Why are businesses moving towards templateless extraction?

As Jishnu said, now is the best time to shift towards templateless extraction due to high ROI. But that’s not the only reason for the shift.

Another key reason is the rise of unstructured and multimodal data. Ninety percent of an organization's data is unstructured. Since many business documents are no longer limited to a fixed layout, processing only documents with predefined templates will cause you to miss most of the important information.

If you’re planning to shift from template-based to templateless solutions, the primary task is to choose a software platform to make the move. You can follow this simple checklist to find the right solution:

☑️ Does the solution offer 95%+ accuracy rates?

☑️ Is the platform easy to use?

☑️ Can the platform handle structured, unstructured, and multimodal data?

☑️ Can the platform support scanned or handwritten documents?

☑️ Does it support matching data across multiple document types in a workflow?

☑️ Is the pricing in your budget?

☑️ Does it comply with your industry’s security standards?

☑️ Can it be integrated into your current tech stack?

☑️ Does it offer reliable customer support?

Once you have identified the solution, you can start moving your documents from the existing setup to the new platform. 

Future-proof your business with templateless extraction

The dilemma between template and templateless is real. 

Businesses tend to start with a template-based solution and keep templateless in the pipeline when things scale. But given how affordable templateless technology has become, it makes sense to adopt it from the beginning.

You’re ready to handle sudden scale, variations in documents, unstructured documents, and multimodal data.