As organizations modernize document workflows, a key strategic question emerges: should you build your own Intelligent Document Processing solution or buy a proven, AI-native platform?
This in-depth analysis compares both approaches over a 5-year Total Cost of Ownership (TCO) horizon, helping you uncover the true costs and ROI behind each option:
- Build a custom platform leveraging tools and services from a hyperscaler (such as AWS, Google Cloud Platform, or Azure).
- Buy a customizable ML-native document processing platform, such as Hyperscience Hypercell.
Based on modeled data and real-world deployment insights, the study reveals how choosing a unified, ML-native document automation platform like Hyperscience can dramatically reduce costs, accelerate time to value, and deliver sustainable performance gains.
Download the full whitepaper to explore how different strategies impact cost, complexity, and long-term business value.
You’ll learn how to:
- Quantify the true total cost of ownership between building or buying an IDP solution.
- Identify hidden costs in engineering hours, infrastructure, and maintenance that impact ROI.
- Understand how Hyperscience delivers 272% ROI and $1.6M in cost savings and performance improvements over 5 years.
- Evaluate time-to-value tradeoffs and performance outcomes across both approaches.
- Make a data-driven decision aligned with your automation and AI strategy.