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These are not your grandmother’s models: the impact of LLM’s on Document Processing

Insight | AI | Enterprise Automation | IDP

These are not your grandmother’s models: the impact of LLM’s on Document Processing

January 22, 2024
These are not your grandmother’s models: the impact of Large Language Models on Document Processing

Document Processing before LLMs

Document processing primarily relies on rule-based systems and keyword matching, which can be effective for structured or even semi-structured documents with predictable formats. However, this approach often struggles with unstructured data, where variability and complexity are high. In contrast, Large Language Models (LLMs) bring a transformative approach to document understanding. They leverage advanced natural language processing (NLP) techniques, enabling them to comprehend context, semantics, and nuanced language variations in documents.

In the ever-evolving world of data science and enterprise automation, the explosive growth of unstructured data generated by companies has been a major challenge for data scientists. To give you a sense of scale, recent studies show we’re likely to witness a surge from 33 zettabytes in 2018 to a predicted 175 zettabytes by 2025. Furthermore, according to Gartner, unstructured data currently represents an estimated 80 to 90 percent of all new enterprise data.  Unstructured data can include conversations through e-mail or text messages, but also social media posts, blogs, video, audio, call logs, reviews, customer feedback, and replies in questionnaires. This trend spotlights an urgent need for more sophisticated tools to create value from this burgeoning data deluge.

Our team has over 5 years working with various OCR and NLP technologies, including having developed and training models in-house.  Don’t get me wrong, IDP  tech has come an extremely long way and the tools have gotten tremendously powerful. Libraries such as Amazon Textract (among many others) provide ML engineers a powerful suite of tools to accelerate the speed and quality of applying intelligent document processing to automation scenarios.

However, there are still limitations to how IDP can be adopted to a range of automation scenarios that we encounter in enterprise environments.

Think of traditional models document processing tech as a diligent yet somewhat myopic librarian, meticulously following rules but often missing the bigger picture. In contrast, Large Language Models (LLMs) are like Sherlock Holmes — insightful, context-aware, omnipresent, and adept at deciphering the most cryptic of texts.

This results in several key benefits and improvements:

Enhanced Comprehension

Traditional Method: Typically relies on keyword spotting and pattern recognition. For example, extracting dates or specific terms from structured forms.

LLMs Approach: Goes beyond mere pattern recognition. It interprets language nuances and intent, essential in contexts like financial and legal document analysis where the meaning of clauses and data can be complex.

Flexibility with Unstructured Data

Traditional Method: Struggles with documents like unstructured emails or reports, often leading to high error rates or the need for manual intervention.

LLMs Approach: Excel in handling unstructured formats. For instance, in customer service, LLMs can analyze and respond to diverse customer queries that vary in structure and content, easily extract information from employment letters or mortgage commitment statements.

Dealing with unstructured data, which includes everything from casual emails to social media chatter, videos, and customer feedback, is not a trivial matter. This kind of data resists neat categorization and defies traditional database structures, posing significant challenges in analysis and comprehension. Here’s where Large Language Models show their mettle, adeptly navigating this complex, non-uniform data and unlocking valuable insights that conventional methods might miss.

Adaptive Learning

Traditional Method: Updating rule-based systems for new formats or languages is time-consuming and resource-intensive.

LLMs Approach: Can continuously learn from new data, adapting to changes in language usage or document formats without extensive manual reprogramming.

Error Reduction

Traditional Method: Prone to errors in cases of ambiguous or context-heavy information, resulting in lower reliability.

LLMs Approach: Their deep contextual understanding leads to more accurate data extraction and interpretation, crucial in high-stakes industries like legal, financial and healthcare.

A Practical Example

ChatGPT 4, without any specific fine tuning or pre-training is able to easily extract information from a document it has never seen before. It understands the context and you can simply query in a natural way for data points that you are interested in:

*Chat gpt extracts information_Blanc Labs

* Note: we take data privacy and PII seriously (see below) and created “spoof” documents for the purposes of this demonstration.

For instance, by asking direct questions such as ‘What is the policy end date?’ or ‘By what margin has the insured amount varied?’, it promptly delivers precise information with perfect accuracy.

This scenario offers the opportunity to further explore solutions that leverage the unique capabilities of LLM’s for the purposes of intelligent document processing and automation.

Generative AI-Powered Extraction and Comparison of Insurance Policy Documents

In the previous section, we delved into the capabilities of Language Learning Models (LLMs) in streamlining the extraction of key information from various document types. To demonstrate this further, we now present a practical application of our system.

The first part of the demonstration involves uploading the initial insurance policy, which acts as our benchmark document. Watch how the system seamlessly processes this document, effortlessly extracting critical details such as the policy number, coverage specifics, the insured party’s information, and other essential data.

Next, we upload a second document representing a modification in the policy. It not only extracts pertinent information from the new document but also conducts an intelligent comparison with the original policy. Notice how the system highlights the changes in the date and insurance limit. This comparative analysis is vital to ensure comprehensive and accurate updates of all modifications and their implications.

To enhance the efficiency of such systems, integration with existing databases and cloud storage services is key. Utilizing APIs, these systems can automatically retrieve documents from various sources such as cloud storage (like AWS S3, Google Cloud Storage), internal databases, or even directly from email attachments. This integration enables real-time processing and updates, ensuring that the latest documents are always analyzed and compared.

The Role of Retrieval-Augmented Generation (RAG) in LLMs

For more context specific answers and solutions, Retrieval-Augmented Generation represents a significant advancement in the capabilities of LLMs. It’s another step forward on this never-ending roller coaster!

  • Enhanced Accuracy and Relevance: RAG combines the generative power of LLMs with information retrieval, pulling in relevant data or documents to provide contextually accurate responses. This is particularly beneficial for financial analysis and reporting, where accuracy is paramount.
  • Dynamic Data Integration: Unlike traditional LLMs, RAG can integrate real-time data, offering dynamic responses to financial queries. This is essential in finance, where market conditions and regulatory environments are constantly evolving.
  • Customized Financial Advice: RAG’s ability to retrieve and process vast amounts of data allows for highly personalized financial advice, tailored to individual customer profiles and market conditions.
  • Improved Compliance and Risk Management: In the regulatory-heavy landscape of financial services and healthcare industries, RAG can efficiently process and cross-reference internal and external data sources including detailed regulations and requirements. We believe that there is a huge opportunity to automate regulatory, risk, and compliance checklists to reduce complex manual efforts that exist in regulated industries.

Potential limitations of deploying LLM’s for document processing (at scale)

While LLMs are highly likely to revolutionize document processing with,  it is important to consider potential limitations as well. LLMs are like a double-edged sword, powerful in processing vast amounts of data but requiring careful handling to address privacy concerns and manage computing resources.

  • Privacy and Personal Identifiable Information (PII): LLMs are capable of processing vast amounts of data, including confidential or proprietary information as well as PII data.  Organizations must work within data security frameworks and engineer solutions that have data security at the core of how they are designed and deployed.  As a SOC2 Certified company, this is an area of key focus for our teams and we have implemented robust data handling and processing protocols to ensure that all PII is managed securely and in compliance with privacy regulations.
  • Computing Power and Cost: The potential impact offered by powerful LLMs to read and extract data from large volumes of unstructured data is reliant on the on substantial computing power required to run these models.  We are still in the early stages of enterprise adoption of generative AI technologies and the economics of leveraging these toolsets at an enterprise scale are fairly dynamic.  We expect a lot to change over the next few years but in the meantime, we are actively working with clients to understand the business drivers of using LLM’s to automate processes.  With our deep background in intelligent document processing we’ve become experts at crafting solutions that optimize model efficiency without compromising performance. We employ techniques like model pruning, efficient data processing pipelines, and cloud-based solutions that balance computational demands with cost-effectiveness.

Conclusion

LLMs and RAG are the vibrant threads bringing new patterns of efficiency, accuracy, and innovation. We’ve journeyed from the meticulous yet narrow pathways of traditional methods to the expansive highways of AI-driven solutions. This evolution isn’t just a step forward; it’s a quantum leap into a future where data isn’t just processed but understood, where advice isn’t just given but tailored, and where compliance isn’t just followed but mastered.

The advancements in unstructured data analytics signal a critical shift in our approach to data. It’s not just about the volume; it’s about the untapped potential that lies within. This raises a compelling question: how can we leverage unstructured data to gain a deeper understanding of our customers, societal trends, and the world at large? The key lies in harmonizing cutting-edge AI tools like Large Language Models with human insight, transforming this wave of data into insightful and actionable knowledge.

Harness the power of AI

At Blanc Labs, we specialize in tailoring AI solutions to the specific needs of the Canadian financial and healthcare sector. Our expertise in AI, automation & digital product development positions us to assist in harnessing the power of LLMs and other AI technologies. We provide customized solutions for intelligent document processing, intelligent automation, and enhancing customer experiences, ensuring compliance with industry standards and regulations.

Explore how Blanc Labs can assist your organization in navigating and succeeding in the digital era.

Author

Luciano Lera Bossi
BPI & Intelligent Automation Lead

Luciano Lera Bossi is a skilled Engineer with 15+ years of success in tech, specializing in Intelligent Automation, Low Code/No Code and Agile Project Management. He enables effective communication between technical and business stakeholders, resulting in seamless project outcomes.

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From Chaos to Clarity: Achieving Operational Excellence through Business Process Improvement

Financial Services | Business Process Improvement | Enterprise Automation

From Chaos to Clarity: Achieving Operational Excellence through Business Process Improvement

January 18, 2024
Business process improvement at work_Blanc Labs

Generative AI and Automation: Are you implementing them effectively?

The emergence of exponential technologies like Generative AI has sparked enthusiasm among companies and executives, who see the potential for enhancing operations and adding significant value to their businesses. In a PWC survey¹, 86% of U.S. executives projected AI’s transition into a ‘mainstream technology’ within their companies in 2021. Moreover, 25% of businesses utilizing AI anticipate revenue growth.

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The Cost of No Change

Every business, regardless of its size or industry, operates within a complex web of processes. These processes, when left unoptimized, can lead to chaos, inefficiency, and missed opportunities. Employees may find themselves bogged down in manual tasks, information silos, and redundant workflows. Meanwhile, customers may experience reduced satisfaction due to prolonged or unclear processes and excessive touchpoints, potentially leading to attrition. This chaos not only hampers productivity but can also erode customer satisfaction and profitability.

 

¹ PricewaterhouseCoopers, “PWC 2022 AI Business Survey”, online: PwC
²“Gartner says nearly half of CIOs are planning to deploy artificial intelligence”, (13 February 2018), online: Gartner

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Employees lose 26% of their day to avoidable chores.

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Each employee costs $4,129 and 42 days to be trained.

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³Saunders, Dave, “How Much is Inefficiency Costing Your Business”, (19 November 2020), online: Electronic Data
Capture, Mobile Data Collection – Array Survey App

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Download the Full Whitepaper

From Chaos to Clarity_Business Process Improvement_Blanc Labs

Our teams have compiled insights and best practices in this practical and outcome focused whitepaper.  Our learnings are based on numerous successful client engagements, research, and industry partners.

Business leaders seeking practical advice to advance their BPI capabilities will find value in the topics covered in the whitepaper.  These include:

  • A step-by-step approach on how to conduct Business Process Improvement within an enterprise operating environment
  • Practical implications of using Business Process Improvement with Intelligent Automation
  • Case Studies on the successful use of Business Process Improvement in mid-sized to enterprise organizations

 

From Chaos to Clarity

 

You consent to receive communication from Blanc Labs by providing us with your contact information. You can unsubscribe at any time. Please review our Privacy Policy for further details. 

Authors:

Luciano Lera Bossi
Luciano Lera Bossi
BPI & Intelligent Automation Lead

“Our commitment is to evolve your business processes in a way that’s both data-driven and adaptable, fostering an environment where continuous improvement is the norm, and each step leads to a more effective and empowering operational experience.”

David Liu
David Liu
Lead-CoE Consultant

“In the race for growth, inefficiencies hold companies back. Success unfolds in continuous refinement—where processes evolve, innovation thrives, and excellence becomes ingrained.”

Meet David Liu: COE Lead, Process Improver, and Ramen Aficionado 

People & Culture | Business Process Improvement | Enterprise Automation

Meet David Liu: COE Lead, Process Improver, and Ramen Aficionado 

December 6, 2023
David-Liu Profile_Blanc Labs

Say hello to David Liu, our new BPI CoE Lead! He’s the kind of guy who’s just as excited about diving into complex enterprise processes as he is about making a bowl of handmade ramen (his absolute favourite). His insatiable curiosity propels him to delve deep into the essence “why?”, and an expert at finding ways to enhance and elevate outcomes.

David’s been on quite a journey for the past three months, settling into his new life in Canada and shaking things up here at Blanc Labs. We sat down with him to find out more about his experience and discover what fuels his passion to understand the inner mechanisms of both professional landscapes and culinary delights.

Six Questions with David Liu

Welcome to Canada and to Blanc Labs! How have your first 90 days been?

Wow, these past months have been quite the ride, packed with trust-building, blending into new cultures, and loads of personal and professional growth. Shortly after my onboarding, our team kicked off a fairly large Business Process Improvement (BPI) project and and formalizing the BPI practice within Blanc Labs has been a great experience. Each step of this has been a building block for me.

As someone who recently moved from Hong Kong, I’ll admit, I had my doubts about adapting to a whole new workplace culture. But the moment I stepped into Blanc Labs, the team made me feel right at home. They handed me the reins, offering the freedom and trust that allowed me to make a significant impact around here.

Any standout moment that you’d like to tell us about?

One standout moment was a business trip to Vancouver, where I conducted an on-site process assessment for a client. This firsthand experience not only deepened my understanding of client needs but also helped me form close relationships. With the collaboration of experts from different areas at Blanc Labs, we successfully delivered our first BPI project, receiving recognition from the client—an auspicious start for the BPI practice.

What attracted you to Blanc Labs in the first place, and why did you choose to join at this point in your career?

Blanc Labs provides a dynamic, startup-like environment with daily challenges, which I find invigorating. The rapid pace and expansive growth opportunities align with my career goals. More importantly, the shared vision on business process improvement during the interview resonated with me, making it an easy decision to join a team that values innovation and is willing to take risks.

What makes Business Process Improvement such an interesting area of work for you?

My career in the process-related field comes from a simple desire—to streamline processes and make everyone’s work easier. Growing up, my curiosity about how things work, be it a restaurant kitchen or a car engine, fueled my interest in operations behind businesses. This fascination deepened as I came across more slow processes in daily life. That’s when I knew I wanted to pursue consulting and specialize in business process improvement.

How do you envision the future of BPI, and what challenges do you foresee?

Even as I envision an automated future where most tasks are streamlined, I believe human intervention will remain crucial in customer-facing roles and creative industries. Because of automation, there is a concern about potential job loss. Post-improvement initiatives, companies must consider upskilling employees or transitioning them into roles that leverage human intervention, like customer-facing roles, to maintain value addition.

And finally, what according to you, makes a Business Process Improvement project successful?

I like to think of a successful BPI project as a well-made bowl of ramen—

The flavorful broth needs a long time to boil bones and meat until they blend well for a rich flavor. This is like the experience needed for a good BPI project. Finding issues and understanding process problems takes years of practice and dedication.

The Tare, though a small part in ramen, has a big impact on the noodle’s taste, determining the overall flavor. It’s similar to the goal in a BPI project. A goals acts as the guiding star throughout, leading us to the expected business outcome. A BPI project without a clear goal is like ramen without Tare—it lacks flavor and excitement.

The type of flour used in making noodles is comparable to the tools and methodologies employed in the analysis. Meanwhile, the texture and thickness of the noodles resemble the direction of the analysis. For a successful BPI project, leveraging experience to select the most suitable tools and methodologies is crucial. This strategic choice ensures accurate analysis, aligning with the project’s goals effectively.

In ramen, oils and fats serve to enrich the broth’s flavor, adding complexity to the overall taste. Similarly, in the realm of BPI, user education plays a vital role. If users are not well-informed about the new process, they may prefer the original one, rendering the efforts of the entire project futile.

Finally, the toppings on the ramen symbolize the selection of technologies. Just as there can be an infinite combination of toppings in ramen, choosing the right set is essential to enhance the overall flavor. Similarly, in a BPI project, technologies act like toppings strategically added to enrich the final product.

 

David Liu_Ramen Process_Blanc Labs

David Liu’s Ramen Making Process

“Ramen is my go-to favorite, and exploring great ramen spots in downtown Toronto has been so much fun. Now, a quick heads-up—I’m not a pro chef, just a big ramen fan who enjoys watching ramen videos online.

So, here’s how you make it. First off, you start with making the broth. Boil stuff like bones, meat, and extra flavors to get a yummy base for your ramen.

Then comes the Tare, which is the seasoning. It’s usually made with soy sauce, salt, or miso. You mix it into the broth to amp up the flavor.

Next is making the noodles. Mix flour with water (sometimes carbonated water), stretch the dough, and cut it into noodles.

To make the broth richer, add some fats and oils. It gives the ramen that extra deliciousness.

Finally, to make it look cool and taste even better, add toppings like pork, seaweed, bamboo shoots on top of the noodles and broth. It’s like the cherry on top, making your ramen not just tasty but also a feast for the eyes.”

Feeling inspired by David’s journey? Want to supercharge your own business processes? Whether you’re craving insights on enhancing workflows or simply curious about David’s favorite ramen spots, he’s your go-to person! Reach out to David at davidl@blanclabs.com.

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Shannex Adopts Automation to Revolutionize its Employee Experience

Healthcare | Enterprise Automation | Healthtech | RPA

Shannex Adopts Automation to Revolutionize its Employee Experience

November 7, 2023
Shannex building

Engagement Summary

Shannex  is a leading provider of seniors’ care, service and accommodation across its 47 long-term care and retirement living communities in Nova Scotia, New Brunswick and Ontario.

People are at the core of Shannex’s mission, vision, and values to lead the way to better living for individuals and the communities the company serves.

Like many health care organizations in Canada, Shannex is experiencing an increased demand for health care workers and needed a solution to improve operational effectiveness to bring more employees on board in a more timely and efficient manner.

The employee onboarding process involves multiple departments and is prone to delays, manual errors, and access management challenges. These gaps did not allow new employees timely access to software tools, equipment, and EHR systems. The offboarding workflow, when an employee left or changed roles, also had similar challenges.

Shannex has partnered with Blanc Labs to develop a workflow that leverages Robotic Process Automation (RPA) to improve coordination of task between departments, track onboarding activities and timelines, and manage employee access to new employees or when their role changes.

By partnering with Blanc Labs to map the enterprise workflow across people, processes and technology systems, Shannex expects to see a significant improvement in efficiency and user experience while maintaining system security, leading to higher staff satisfaction and retention rates.

This innovative partnership is being supported by the Coordinated Accessible National (CAN) Health Network – a federally funded organization working to introduce more Canadian technology companies into Canada’s health care system.

Opportunities for Improvement

Shannex’s onboarding workflows presented an opportunity for improvement from both an employee experience and operational efficiency perspective. Manual processing of tasks and multiple stakeholders involved created a high-volume workflow characterized by delays, errors, and information-security risks.

Healthcare
Healthcare
Healthcare
>30%
employees had access to all the IT systems equipment they needed on their first day of work.
34%
of new employees experienced delays of more than a week in obtaining all the equipment and system access they needed.
18%
of new hires were less than satisfied with the technology access portion of their onboarding experience.

Shannex partners with Blanc Labs “We relied on Blanc Labs’ expertise and experience to advise us on the internal resources needed to complete the work and to set a pace that would be manageable. The team is extremely knowledgeable from a programming/technical perspective. The technical documentation was very detailed and will be very useful as we grow our internal RPA programming expertise.”

– Christy Nickerson-Rak, Research Specialist at Shannex Incorporated

 

 

 

 

Tech Stack

UiPath Studio
UiPath Orchestrator
UiPath Robot

Expected Impact

Blanc Labs’ RPA-based workflows will reduce demands on operational, HR, IT, and business system teams by automating employee management tasks. This will free up time for business users to focus on higher-value work. Improved accuracy will ensure new employees have the necessary system and equipment access and will lead to higher staff satisfaction and better retention rates.  

Our shared goal is to improve efficiency and user experience relating to employee management tasks.

Banking Transformation Done Right
Your Healthcare Interoperability Partner
woman working
Team working
80%
Reduction in the time required for operations managers to request access to equipment/systems for new hires.
90%
Increase in the level of satisfaction among new hires with the onboarding process.
80%
Reduction in the time spent removing access to systems and equipment for terminations.
60%
Increase in the proportion of new hires with access to systems equipment on their first day in the new position.

Looking Ahead

Through a strategic partnership with Blanc Labs and the CAN Health Network, Shannex is poised to revolutionize its employee onboarding and system access procedures. By integrating technologies like UiPath Apps, UiPath Robot, and UiPath Studio, Blanc Labs has delivered an impactful synergy of automation, innovation, and convenience to Shannex’s employee experience, HR , IT management, and Operations functions.

If you are interested in automating your workflows and improving employee experience, reach out to us at BlancLabs.com and let us explore how we could partner with one another. Contact us today to unlock efficiencies in your processes.

Elevate employee experience: automate, secure, and thrive.

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Low-Code Tools and Automation Power Minor Ailments Program for Pharmacists

November 3, 2023

Blanc Labs teamed up with Daylight Automation (acquired by Quadient) to enable the Minor Ailments service at a major Canadian pharmacy.  The team designed and deployed digital forms, automated workflows, and integrated with enterprise systems to power how pharmacists assess and treat 15 minor ailments at pharmacies across the country. This comes  at a critical inflection point for Canadians needing efficient access to healthcare services.

The client knew having pharmacists fill out a paper-form for each patient would not scale across their network and would create massive headaches for data integration, workflow management, payments & billing, and information security.

With Blanc Labs support, the Pharmacy rolled out a digital workflow solution that offers patients and pharmacists a much improved experience that eliminates extra steps, ensuring accurate and timely assessments, and treatment of minor ailments.

After 6-months of Minor Ailments Service in Ontario

244,630

Assessments Completed

250,150

Prescriptions for Minor Ailments

Benefits of our Solution Approach

Integrated Solution
Streamlined Data Collection
Improved Data Quality & Security
Superior Customer and Employee Experience
Real-Time Updates

Impact

How Blanc Labs transformed for Reliq Health Technologies
85%
Of All Community Pharmacies are Prescribing for Minor Ailments
8
Provinces Currently Allow Pharmacists to Prescribe for Minor Ailments
$42M +
Savings to Ontario with Pharmacists Treating for 3 Minor Ailments

A Transformative Approach to Primary Care

Given that pharmacists are the most accessible health care professionals, I think minor ailments prescribing will lead to an improved pharmacist-patient relationship and a more fulfilling professional career. As medication experts, pharmacists are trained and equipped with the knowledge to practice beyond classic dispensing activities.

Providing clinical services, which allow pharmacists to use their entire range of training, is the future of pharmacy.

When it comes to minor ailments prescribing, passionate pharmacists will be invaluable and I’m hopeful that a shift will occur where these types of services become the norm1.

Timothy Brady, Chair of Ontario Pharmacists Association

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