How document processing evolved into modern input management
Buildsimple over time
- Buildsimple News
Document processing has undergone a fundamental transformation in recent years. In the past, the focus was on fixed rules, standard layouts, and extracting specific pieces of information. Today, the emphasis is on understanding documents within their context, validating information, and using that to determine the next step in the process. For insurance companies, banks, and other document-intensive businesses, this is a strategic development.
It's all about speed, quality, and controllability in core processes. A claim report, a loan application, an email with an attachment, or a change request are often the starting point for important decisions. The faster this information is understood and routed to the right process, the faster companies can respond.
The evolution of Buildsimple illustrates how traditional document processing has evolved into modern input management: from rule-based approaches to AI-powered SaaS platforms, and on to multi-AI and end-to-end automation.
Before 2016: Documents were primarily processed using rules and layouts
For a long time, many companies used systems that processed documents based on fixed rules or known layouts. These systems learned where information was located, how a document was structured, and which fields needed to be extracted.
This worked well for standardized documents. In practice, however, formats, content, and communication channels became increasingly diverse. Documents began to look different. Emails were written in a more informal style. Attachments varied. Customer communication became more diverse.
This gave rise to a new requirement: documents should be understood within the context of the relevant process.
For IT management and operations, this meant that information had to be structured in such a way that it could be verified, processed further, and integrated into target systems.
2016: Machine learning and the cloud are changing the landscape
In 2016, it became clear that machine learning opens up new possibilities for document-based processes. AI approaches helped to understand content more flexibly and categorize information more effectively.
At the same time, the cloud transformed the way software operations were viewed. Individual customer solutions were replaced by a platform that is centrally operated, developed, and scaled.
That was the starting point for a new approach: document processing needed to become operational more quickly, scale more effectively, and offer customers greater flexibility.
For businesses, this step was crucial. Document-based processes needed a reusable foundation so that new requirements could be implemented more quickly.
2017: Buildsimple is launched as an AI-based SaaS platform
Buildsimple was founded within ISR in 2017. The first prototype focused on extracting information from invoice documents.
What began as a clearly defined use case quickly evolved into a broader platform concept. Customer requirements revealed that companies need to extract specific information from documents while ensuring quality and integrating the results into their processes.
This marked a gradual shift from document processing to input management: a structured path from document receipt to the next action.
For our customers, this means that even today, documents are processed as part of a workflow and prepared for the next decision.
2018: Public launch and first demonstration of innovation
Buildsimple was publicly launched in 2018. That same year, Buildsimple received the 2018 AWS ISV Award at the AWS Summit in Berlin for its rapid transition from a consulting-focused business model to a scalable SaaS infrastructure.
The award was an early indication of the technical direction. The key factor was the development behind it: Buildsimple was conceived as a platform featuring reusable functions, governance, and scalability.
What began as just a few microservices has evolved over the years into an AI-based platform for input management. The platform was developed in response to real-world requirements arising from document-intensive processes.
This difference is important to customers. A platform enables reusability, clear control, and a stable foundation for additional use cases.
2019–2021: Initial use cases evolve into core production processes
As the platform matured, the use of Buildsimple shifted more toward core production processes. Insurance companies and financial institutions became particularly relevant because they deal with large volumes of documents, sensitive data, and clear traceability requirements.
In these environments, the entire process is critical: intake, classification, extraction, validation, processing, transfer, and monitoring.
This also led to increased demands on security, integration, and operations. Documents had to be processed in a reliable and traceable manner and integrated into existing system environments.
A new standard has been set for IT and operations: AI must function in production environments. This requires clearly defined roles, stable interfaces, human-in-the-loop processes, and verifiable quality.
2022 to 2024: Multi-AI becomes the operational model
With the development of large language models, AI has become more prominent in many companies. At the same time, it has become clear that productive document workflows require different AI methods depending on the task at hand.
Large volumes of documents often benefit from efficient, specialized models. Complex content can benefit from large language models. Rules and validation processes provide additional assurance. Human-in-the-loop approaches help ensure controlled quality improvement.
This gives rise to multi-AI: various AI methods work together on a single platform, governed by unified governance, versioning, and quality assurance.
This is a major advantage for customers. They can use the AI method that best suits the task, volume, risk, and cost-effectiveness, all while remaining within a manageable platform framework.
Today: Scalability, Quality, and Efficient Operations
Today, Buildsimple operates more than 3,500 AI models for its customers. On average, the platform processes around 500,000 documents per day. At peak times, it has processed nearly 2 million documents in a single day.
These figures illustrate what modern input management is all about: scalability must go hand in hand with security, traceability, and operational reliability. To achieve this, Buildsimple combines specialized AI models, large language models, rules, validation, monitoring, and human-in-the-loop capabilities into a single platform. The goal is a controlled workflow from document receipt to the next action.
For insurance companies, this can help streamline the processing of claims. For banks, it can speed up the processing of loan applications. For regulated companies, it can help manage document-based processes in a more structured, transparent, and efficient manner.
Outlook: From Input Management to Agent-Based Processes
The next step in development goes beyond traditional document processing. Companies want to better recognize, extract, validate, and transfer documents, as well as better coordinate follow-up actions.
That is why end-to-end automation is becoming increasingly important. The process is best concluded at the point where the next business-related action is fully prepared: review, decision, approval, clarification, handoff, or further processing.
In the future, agent-based workflows can help coordinate recurring process steps more intelligently. This is particularly relevant in situations where there are many documents, many rules, many systems, and high requirements for traceability.
For regulated companies, one thing remains crucial: speed must be accompanied by oversight. Productive AI must remain explainable, controllable, and verifiable.
What companies can learn from this trend
Modern document processing is a key operational lever. It influences how quickly departments operate, how effectively operations manage processes, and how transparently decisions are prepared.
Companies should evaluate their document processes by asking themselves five questions:
- Are the documents in the case understood?
- Can new use cases be designed to be reusable?
- Is the right AI method used for every use case?
- Does it include human-in-the-loop, versioning, and monitoring?
- Does the processing lead to the next action?
The key lies in the transition from document to decision. Accelerating this transition improves individual work processes and enhances the responsiveness of the entire company.
Speed is generated at the start of the process
In many companies, documents serve as the initial impetus for decision-making, processing, and customer service. When these incoming documents are structured, validated, and processed automatically, it creates efficiency where it matters most operationally.
Buildsimple was developed in line with this trend: based on practical experience with processes, customer requirements, and the goal of treating documents as the starting point for actionable processes.
This is how document processing evolves into modern input management. And input management becomes a key tool for companies that want to make decisions faster, work more efficiently, and scale securely.
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FAQ
Modern input management refers to the structured processing of incoming documents and information. The goal is to understand and validate the content and route it to the appropriate business process.
Traditional document processing is often heavily rule- or layout-based. Modern processes also require context, AI-based analysis, validation, governance , and a structured handover to target systems.
Multi-AI means that different AI methods are used depending on the use case: specialized models for high volumes, large language models for complex content, rules for straightforward checks, and human-in-thethe-loop for controlled quality assurance.
AI-based input management is particularly relevant for companies that handle large volumes of documents, handle sensitive data, and have high requirements for security, traceability, and scalability. These include insurance companies, banks, and regulated enterprises, among others.
Input management organizes information right at the start of the process. This allows follow-up actions, checks, decisions, and data transfers to target systems to be initiated more quickly and in a more controlled manner.
Short answer
Modern document processing is evolving into input management: Incoming documents are analyzed within the workflow, relevant information is validated, and the data is transferred to the next step. For document-intensive companies, this results in greater speed, improved control, and a robust foundation for end-end-to-end automation.