Buy vs. build: Why in-house IDP development is often an economic grave

Key Takeaways – Executive Summary

• Hidden costs (TCO): The initial costs of an in-house development (“build”) often represent only 20% of the total cost of ownership. Long-term maintenance and technical debt management eat up budgets.
• Time-to-market discrepancy: While specialized IDP platforms (“Buy”) are productive within days, in-house solutions take months to reach market maturity – often with less accuracy.
• The core competence dilemma: IT departments tie up valuable resources in maintaining document pipelines instead of driving innovation in the core business.
• The role of LLMs: Generative AI lowers the barrier to entry for prototypes, but increases the complexity of governance, validation and hallucination control in production operations.

The illusion of control: the appeal of self-build

There is currently a gold-rush atmosphere in many boardrooms and IT departments. Driven by the democratization of Large Language Models (LLMs) such as GPT-4 or Llama 3, the hurdle to automating document processing seems lower than ever before. The hypothesis is often: “Why pay license fees when our developers can build an API wrapper in a weekend?”

This idea is tempting. The initial control over the code, the independence from vendors and the supposed cost savings are strong arguments. In a proof-of-concept (PoC) phase, this approach usually works perfectly. Ten invoices are uploaded and the AI extracts the data correctly ten times. The project is given the green light. But this is where the problem begins. A PoC is not production.

Why in-house solutions fail when it comes to scaling

As soon as the solution is confronted with the reality of input management, the fragility of the “build” approach becomes apparent. The reality is not ten clean PDFs, but thousands of documents with variable quality, handwriting, scans with coffee stains and exotic layouts.

The result is often sobering:

• Maintenance nightmare: Every new document layout requires adjustments to the code or prompt engineering. Your expensive data scientists become “layout janitors”.
• Lack of UI for human-in-the-loop: No AI achieves 100% accuracy. In-house development requires a front end for validation by clerks. Building an ergonomic, high-performance validation interface is often more expensive than the AI itself.
• Integration complexity: The connection to ERP or CRM systems, the handling of webhooks and the guarantee of enterprise-grade security (ISO 27001, C5, GDPR) are often ignored in the PoC.

The market shift: from OCR to intelligent orchestration platforms

Technological change has shifted the parameters of the “Intelligent Document Processing Buy vs Build” equation. It used to be about whether to license an OCR engine or host Tesseract yourself. Today, it’s about orchestration.

Modern IDP platforms are no longer pure extraction engines. They are ecosystems that combine different AI models (OCR, layout analysis, LLMs) and safeguard against hallucinations. Providers such as Parashift have invested years in building a proprietary database (“swarm learning”) that makes it possible to understand document types “out of the box” without the customer having to write a single line of code.

The shift is clear: the current technology (LLMs) has become a commodity. The value is no longer in the model itself, but in the infrastructure around it, which makes the model productive, secure and verifiable.

Cost-benefit analysis: Buy vs. build in direct comparison

For decision-makers, it is worth taking a look at the hard facts. The following table illustrates the discrepancy between perceived and actual costs.

The strategic conclusion: focus on differentiation

The crucial question for you as CTO or IT manager should not be: “Can we build this?” The answer is almost always yes. The question should be: “Should we build this?”

If document processing is not your product that you sell to third parties, it is not a core competency that differentiates. It’s “plumbing” – necessary infrastructure. Just as you no longer program your own email server (because even that would be perfectly feasible today), but instead use Exchange or Gmail, you should also rely on specialized platforms for document processing.

Buying a solution like Parashift is not a capitulation of your own IT, but a sign of maturity. You buy yourself time and stability to use your resources where they create real added value: in the optimization of your business processes and the refinement of the extracted data. If you build today instead of buying, you are investing in the technological debt of tomorrow.