Iron Mountain InSight Intelligent Document Processing whitepaper

Successful organizations can leverage both physical and digital information to make informed decisions, better understand customers, innovate and grow, all while quickly responding to audit requests.

Too much knowledge and information remain trapped because organizations can’t access, comprehend, or use the data contained within documents. But even in organizations digitizing documents, challenges remain in managing unstructured, semi-structured and structured data types in a wide variety of siloed application environments.

The gulf between those organizations effectively extracting, managing, and leveraging their information and those that don’t will continue to widen, as artificial intelligence (AI) and machine learning (ML) are rapidly making their way into every aspect of our lives. It’s an AI world, and successful organizations will harness this technology.

With Iron Mountain Intelligent Document Processing (IDP), you can:

• Quickly turn documents into information you can use by digitizing, extracting, classifying, and verifying information with speed and accuracy, so you can make more informed decisions and enhance customer service.
• Increase productivity by creating your own customized, automated document processing workflows, and/or leverage a team of AI experts, so you can innovate and grow.
• Reduce time, effort, cost, and errors with intelligently extracted and classified data so you can speed time to discovery or audit response.

Iron Mountain InSight Intelligent Document Processing

The evolution of document processing

Optical character recognition (OCR) played a crucial role in initiating the shift towards digital document management, even when physical document handling was still predominant. By converting paper documents into text-enabled formats, OCR facilitated their integration into enterprise document management systems. However, the primary focus of these early systems remained on document storage and retrieval. Although this was a significant advancement, it still necessitated further steps to structure, enrich, and tag the information for optimal utility.

Document and information management has grown, fueled by the efficiency and productivity gains that electronic records could provide, but it was the addition of machine learning (ML) that truly unlocked the opportunity. By adding intelligence, through AI and ML, a new generation of document management has emerged: Intelligent Document Processing (IDP).

Iron Mountain InSight IDP includes high-speed scanning, data extraction, classification and enrichment. Human in the loop (HITL) is available to manage exceptions and to refine and retrain AI models leveraged in the system. The document processing workflow can be customized for your specific workloads, applications and environment via managed services. Or, you can create your own document processing workflow in the low-code development environment with an AI model library, tools for labeling and training, monitoring and exception processing.

InSight IDP is part of Iron Mountain InSight Digital Experience Platform (DXP), our scalable end-to-end software-as-a-service (SaaS) platform. The modular platform allows you to incorporate digital and physical Content Management and Information Governance capabilities to transform your information experience.

The Intelligent Document Processing platform

The Iron Mountain InSight IDP platform is designed to integrate into an organization’s content management and document workflows, providing intelligence that spans from ingestion of information through to data visualization and processing automation. Key elements of the platform include accuracy, efficiency, predictability, and visibility—areas where an IDP solution needs to be able to scale—to meet not only the needs for today, but also the needs of the future.

The entire orchestration of the solution is broken down into six phases, Import & recognition, Classification, Data extraction, Enrichment, Human-in-the-loop, and finally Integration. Each of these steps is critical to the overall accuracy and effectiveness of the solution.

Import and recognition

The first step in orchestration is importing the documents, often transitioning them from physical to digital. With high-speed scanning or computer vision, teams can ingest information into the system. Metadata, and data about the document is collected and stored.

Classification

Once in the system, the classification task can begin. In this step, the document’s structure and content are classified and information is validated. If there are separator sheets tied to the document ingested, these are removed to help streamline/optimize the process.

Data extraction

In this step, document types are aligned with applicable ML models that have been trained on that document type, enabling the system to extract information directly from the document, including fields like names, addresses, dates, currency amounts, and more. As the models have been trained to know where the content lies within the document, automating the extraction. Intelligent annotation is used to help extract unstructured data and information that can be used to help in the secure training and optimization of the machine learning models.

Enrichment

During the enrichment phase, the system adds structure, context, and metadata to information to make it more usable. The resulting enriched data can then enable better automation outcomes, e.g. invoices are accurately paid and reconciled on time.

Human-in-the-loop

While the capability and speed of ML models can aid in the automation of the process, humans in the loop can handle the exceptions, and perform quality control.

Integration

Finally, after the data has been ingested, properly categorized, organized, and validated, it is then ready to be integrated back into the Iron Mountain InSight Content Management platform, or other document or data repository.