How Parse2ERP's Flexibility and Customer Support Drive SaaS Scaling

I was working with a chartered accountant's team where they mentioned that most PDF parsers don't save time much, as the PDF parser parses text from the PDF with or without OCR, but still end users keep copying required data to Excel from extracted markdown or JSON. That's when we decided to plug in Python libraries to extract text, but then it allows users to write labels that they want, data that they need, all returned with a Python script, so that users can just upload PDFs and, based on configuration per detected template, it provides a clear CSV file with all data. The customer loved it, and we have added the following features in the current version: - User can return multiple times and then have a line items type of structure required for ERPs. - We have integrated an option to add a file in software that can be accessible to enrich data. - User can add logic for data to be fetched in the initial script. - Make global methods to avoid repeated steps in template mapping. - Finally, if a user is using ZOHO Books, they can directly upload bills + attachments directly in ZOHO too.

Worked, We assisted the customer with invoice reconciliation in our software and that helped us with more word-of-mouth marketing. - We started offering demos/trials for free, which worked for us as most of the clients that use this would be locked in at a higher price too. Quick response support from our team helped clients more compared to competitor solutions. - Providing a phased transition to clients gained more trust compared to asking them to commit 100% to migration from their current in-house process. Flopped, We tried cold mailing, but Outlook and Gmail started landing our mails in spam; our domain reputation decreased. - Running generic campaigns on leads without addressing any industry pain points did not result in any leads. - We tried offering discounts upfront with no trials, where people did not give much response to our campaign. Paid campaigns led to clicks but not any series of buyers.

One of the most common complaints from customers is that they do not have technically skilled staff to handle this software. Many clients initially assume that the software requires hiring developers, which created initial hiccups during the onboarding. To handle this, we simplify the process as much as possible. We created detailed step-by-step documentation to explain to customers how they can make templates in a business environment. We told the customers that they are not required to learn Python programming for their setup. Instead, they can simply tell their requirements to AI in plain English and get back the template code for the same. We even offer sample boilerplate code for customers inside the software so they can see how to apply logic for extraction. This changed customer perception significantly. Instead of seeing this as only a developer's tool, they started viewing it as an operational productivity tool. As a result, customers became more willing to go for automation.

Most people in this market think one UI and fixed workflow can solve all RPA automation problems. But actual businesses work very differently from each other. Every company has different processes, different approvals, different file formats, different people handling work. Because of that, automation software without coding flexibility becomes a limitation very fast. In our opinion, automation tools should always provide some coding or advanced customization layer. As an automation service provider, saying "this is not possible in our software" should not become a common answer. Businesses expect software to adjust according to their workflow, not the opposite. Another thing people get wrong is thinking cloud-based extraction products are always better. In many real business cases, offline sovereign extraction is more useful because companies care about privacy, control, speed, and stability. Especially when handling invoices, pharma documents, or internal reports. People also focus too much on UI and UX in extraction products. Good UI matters, but after some time, customers mostly ask for deeper customization, advanced logic, and the ability to handle edge cases. Fancy interface alone does not solve operational problems.

We are planning to add support for more ERP systems because many customers are asking for integration with their existing software. We are also working on supporting different Excel and CSV formats because every company keeps data a little differently, and fixed export formats create issues for them. We are also trying to support more file extensions and document types so customers can process a greater variety of files within the same workflow. Another focus is improving customization options because many businesses need small changes according to their internal processes. We are also looking into making setup easier for non-technical users while still keeping advanced options for power users. Right now, many automation products either become too simple or too technical; we are trying to balance both sides. The main goal for the next months is to make the software more flexible for real business use cases instead of only looking good in demo videos.

Right now, the system handles a few thousand PDF invoices every day across different enterprise setups. In most cases, it’s deployed on internal VMs managed by the client side, and the application uses Python automation together with local compute resources to run large-scale extraction and invoice validation tasks.

We have massive experience in extraction knowledge based on Python and VBA. While the software itself is built from scratch, we have vast experience working with other projects from the last 10 years. Based on our knowledge and our work with clients on real hands-on experience and enterprise data, we can gauge how we can turn our scattered knowledge into one final product that supports the extraction of PDFs, not just for invoices but for any kind of documents. We are an automation-first company; hence, while the software usually falls into the CRM category where humans feed data and top management can see summaries, our software extracts information from PDFs and other documents, actually reducing the workload on users.

I spent 4 months preparing a PDF overlay that allows selecting a region to fetch text, and then it turned out that even fetched text from a PDF needs treatment to make it ERP-ready. That's when it hit our team that the extraction products are not supposed to be easy, not just supposed to have an attractive UI, but need to offer advanced capacity to cover any kind of use case that customers may be facing in daily life. Also, people undermine the amount of hands-on training that needs to be provided to end users; hence, do not spend more time on manuals and literature. Customers will be asking for support anyway.