Getting Your Documents AI-Ready: Here Is How

While the buzz around AI is putting pressure on IT leaders and data engineers to kickstart and successfully implement AI projects, they are facing challenges when it comes to preparing the data for AI-readiness. One of the biggest pain points that these leaders have yet to solve is dealing with unstructured data in company documents, which actually makes up around 80% of an organization's total data.

In a recent live session with data experts, we focused on how to boost digital transformation, automation, and AI efforts by preparing and managing document data for AI readiness using advanced document transformation techniques.

Let's start with the basics.

3 Biggest Reasons Why It Is Difficult For AI To Read Your Documents:

1. Lack of predefined format: Unstructured data, like text or images, that is hidden inside unstructured document formats such as Word, TIFF, or Emails, lacks a predefined format or organization. Unlike structured data, which is neatly organized in databases or spreadsheets, unstructured data exists in a more free-form manner. This lack of structure makes it challenging for AI systems to interpret and analyze the data effectively.
   
   
2. Data volume and accessibility: Unstructured data can be quite voluminous, especially in large organizations or regulated industries that heavily rely on documents. Additionally, this data can be hidden away in unstructured or legacy formats and siloed systems, making it inaccessible for AI platforms.
   
   
3. Data integration and interoperability: Integrating unstructured data with other structured or semi-structured data sources is often necessary to gain comprehensive insights. However, this can be a challenging task due to differences in data formats, schemas, or data models. Ensuring interoperability and seamless integration between structured and unstructured data sources is crucial for effective AI applications.

By addressing these challenges and finding solutions to make unstructured data more AI-friendly, we can unlock the full potential of AI in document analysis and insight extraction while driving digital transformation in industries such as life sciences, manufacturing, energy and insurance.

Let's look at key takeaways from our live session that demonstrated best practices to tackle the unstructured data problem and increase efficiency of your document workflows.

3 Ways To Solve Unstructured Data In Documents For AI

Takeaway 1: Adlib Software is a tool that automates the process of standardizing complex, unstructured digital data into structured documents that are compliant and AI-ready.

Kunal, a Product Manager for Adlib Software, explained that the software acts as a middleman, taking in unstructured data from a variety of document types and sources, and transforming it into structured, standardized documents of record.

"We like to take all of those complex data variables, all of that unstructured data, and bring them into our software, where we really act as a piece of middleware," Kunal said. He emphasized that Adlib prides itself on being able to handle a wide range of over 300 different file types, ensuring that the software remains versatile and valuable to a wide variety of businesses.

Kunal also highlighted the software's ability to automate complex business tasks, such as merging documents, applying watermarks, headers, and footers, and validating documents against specific technical criteria. This helps to create a highly efficient, repeatable process that can handle a large volume of documents, and significnatly improve standardization across your enterprise. Kunal said, "We want to take all of those documents, pull them from all of those sources, do everything that needs to be done with assembly steps to create your documents of record, and then place them back where they need to go."

Takeaway 2: Adlib Software seamlessly integrates with an organization's existing systems and is easy to use.

The admin experience with Adlib Software is designed to be straightforward and user-friendly, according to Anthony Vigliotti, the Chief Product Officer at Adlib Software. He pointed out that the software allows admins to easily establish job acceptance and transformation rules. "What we want to do is allow you two sets of rules. First and foremost, your job acceptance rules, which is the job admin rules, and your transformation rules," said Anthony.

Kunal further demonstrated how easy it is to establish a connection with an existing system, such as Microsoft SharePoint, to ingest documents. Once documents are ingested, the software allows users to define what actions should be taken on the documents, such as applying footers or changing font sizes and colors. Kunal said, "What we really aim to accomplish is make this as user friendly, simple, and straightforward as possible."

Takeaway 3: Adlib Software provides robust analytics and monitoring capabilities, ensuring transparency and effectiveness in processing documents.

Adlib Software offers real-time and historical data analytics, granting admins insight into the system's performance and efficiency. Kunal explained, "What this is showing me is, if this is a job status table, consider this to be like an engine status table. Now, where this is showing me with my one engine, what documents is it working on? Where are those documents coming from?"

The software also provides a consumption-based model, offering transparency on the amount of pages processed through the system. This allows organizations to measure the value they are getting from the software based on their specific usage. Kunal added, "We have transitioned to more of a consumption-based model, then number two is based on, you've seen all these different features. You've seen all these different features... we start to develop from a bundling and pricing perspective."

In addition to its built-in analytics dashboard, Adlib can also integrate with existing application performance monitoring tools, providing flexibility for organizations to monitor the software's performance in a way that suits their existing tech stack. Kunal stated, "We have transitioned towards that, it's entirely mission critical that that is completely transparent just in terms of the amount of pages that are processed and making sure that's accurately displayed and counted."

Must Have Document Transformation Functionalities For AI-Ready Documents

• Adlib Software supports a wide range of over 300 different file types, allowing for flexibility in managing and processing documents.
• The software ensures 100% conversion fidelity, maintaining the exact layout, fonts, and elements of the original document in the converted version.
• Adlib Software allows for the automation of complex business tasks, improving efficiency and reducing the risk of human error.
• The software can connect to various document management systems and core systems within business applications.
• Adlib Software provides a robust monitoring experience, with real-time analytics and historical data to track the system's performance and efficiency.

Why Adlib

Leveraging AI to analyze and make sense of unstructured data in documents is a total game-changer for businesses aiming to improve data-driven decision-making and achieve operational excellence. Adlib is focused on delivering solutions to enable companies to do exactly that.

Adlib is a tenured partner of many global organizations in highly regulated industries, helping them scale operations and modernize their tech stack for growth. Adlib's advanced document transformation is a standard of document management strategy and a business necessity.

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