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What if your document processing system could do more than categorize documents and extract data, no matter the format? That’s exactly what you can do with intelligent document processing (IDP) software. IDP tools adapt to varying structures and formats and understand content to summarize lengthy documents, identify anomalies, and flag errors. The best part? IDP software continuously improves in accuracy the more you use it.

When AI first started to gain widespread adoption, it sparked a wave of fear. While much of that fear was overblown, we still need to remain cautious about any new technological innovation. Given AI’s potential to drive change on a massive scale, applying ethical principles to AI is not just important, but urgent. Every company must prioritize responsible AI—not only as an ethical responsibility but as a practical, strategic choice.

ERP systems are critical in government agency operations for integrating internal and external management information. They are intended to optimize processes, improve collaboration, and connect with customers, vendors, and partners. Government ERP systems typically include modules related to financial management, human resources, sales, procurement, inventory, and operations like contract and project management.

The computer revolution in law took flight in the 1970s with the release of the iconic red “UBIQ” terminal. This innovation completely changed how legal document management was performed. It empowered lawyers to easily browse case law online rather than looking through towering racks of yellowed paper. As the years passed, a wave of new document management solutions emerged.

Let’s be honest – AI can seem like a bit of a mystery, and with this mystery comes myths and misconceptions. Is it actually that good? Can it handle varying document structures? Can it integrate with my existing systems? Because of this mystery, many companies have yet to take the leap and incorporate AI into their data processes. Today, we’re going to play MythBusters, separate fact from fiction, and show how you can use AI document processing to maximize efficiency and save costs.

Healthcare data is set to soar, with projections showing that it will grow from 2,300 exabytes in 2020 to an impressive 10,800 exabytes by 2025. To put that in perspective, that’s like having enough data to fill over 2.5 billion DVDs! What’s more is that a large portion of this data is unstructured—scanned documents, handwritten notes, and PDFs that don’t easily integrate into traditional systems. This is where Intelligent Document Processing (IDP) comes in.

Many vendors have started calling their platforms “low-code” or “no-code.” Competitors often pit the terms against each other. But what do low-code and no-code really mean? And what's the difference between the two? Both platforms offer improvements over traditional high-code approaches. The biggest differences are the target user groups.

What’s one thing all your favorite legal shows have in common? Whether it’s Suits or The Lincoln Lawyer, they rarely show the amount of paperwork lawyers have to handle on a daily basis. Understandably so, paperwork isn’t the most glamorous part of the job but that doesn’t mean it’s not crucial. In fact, lawyers deal with tens, if not hundreds, of documents on a daily basis during most parts of their job, such as discovery, research, or drafting.

In the world of LLMs, size doesn’t matter. It’s how you generate output that counts. Generative AI (GenAI) adoption rate in organizations jumped from 33% to 65% this year, which means if your organization isn’t leveraging AI, it’s time to get on board or get left behind. One powerful way enterprises are leveraging GenAI is by training and deploying private Large Language Models (LLMs).