AI and LLMs are not just a technological leap; they’re a strategic imperative. By embracing this evolution, businesses gain a distinct advantage—staying ahead of the competition, enhancing stakeholder experiences, and optimizing both time and costs. In this white paper, we explore our top LLM business applications.

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Top LLM Business Applications Introduction

In the landscape of modern artificial intelligence (AI), Large Language Models (LLMs) have emerged as a transformative force, poised to revolutionize industries and redefine the boundaries of what’s possible. As a corporate executive, embracing LLMs is not just about staying ahead of the competition; it’s about shaping the future of your industry. By harnessing the power of modern AI and LLMs, you empower your organization to:

  • Enhance Stakeholder Experience: Deliver exceptional customer experiences, maintain strong investor relationships, and foster a collaborative workplace culture.
  • Optimize Resource Allocation: Streamline operations, reduce costs, and maximize resource utilization, driving profitability and financial sustainability.
  • Accelerate Innovation: Uncover new opportunities, develop disruptive products and services, and establish your organization as a leader in innovation.

Embracing LLMs Responsibly

Modern AI’s potential for transformative impact is undeniable, and LLMs are a key component. However, it’s crucial to approach this technology with caution and responsibility. By addressing biases, promoting transparency, and prioritizing human oversight, we can harness the power of LLMs to drive positive change while safeguarding against potential risks. Here are some specific challenges businesses face when adopting LLMs and AI in general:

  • Skills and expertise: Businesses may lack the internal expertise to develop, implement, and maintain AI systems. They may need to hire or train employees with the necessary skills, or partner with external AI experts.
  • Data quality and preparation: AI systems require high-quality data to train and operate effectively. Businesses may need to invest in data cleansing and preparation to ensure their data is suitable for AI applications.
  • Integration with existing systems: Integrating AI systems into existing IT infrastructure can be a complex and costly process. Businesses may need to invest in new hardware and software to support AI workloads.
  • Ethical considerations: Businesses need to carefully consider the ethical implications of AI use, such as data privacy, algorithmic bias, and transparency. They should establish clear ethical guidelines and ensure that AI systems are used responsibly.
  • Legal compliance: Businesses need to comply with all applicable laws and regulations related to AI use, such as data privacy laws and anti-discrimination laws. Given how quickly the landscape evolves, it is critical to understand not only current, but future legal implications for these technologies.
Top LLM Business Applications graphic showing cartoon figure looking at different LLM logos

Custom Deployments Deliver on the Promise of AI

While off-the-shelf LLM solutions offer a quick and convenient entry point, they often fall short in addressing the unique needs and challenges of specific businesses, and their inner workings may be obscured, potentially creating risk. This is where custom LLM solutions come into play. Tailored to the precise requirements of an organization, custom solutions provide a level of flexibility, adaptability, and scalability that pre-built solutions simply cannot match.

Custom LLM solutions allow businesses to harness the full potential of AI by aligning it with their specific goals, data, and infrastructure. This personalized approach ensures that AI is seamlessly integrated into existing workflows, maximizing its impact and minimizing disruption. Moreover, custom LLM solutions undergo rigorous testing and refinement to ensure accuracy, reliability, and consideration for ethical implications, mitigating potential risks and fostering trust among users.

Mosaic has been applying machine learning (ML) and AI technology to deliver custom solutions for our clients since 2004. Even though this technology has changed with the advent of LLMs, our diligence in matching the proper predictive/prescriptive analytics to specific decisions has not.  As we work with corporate customers eager to unleash the potential of this technology into their operations, we have come across 5 common Top LLM Business Applications for any industry.

Finally, let’s get to our list of Top LLM Business Applications:  

  1. Enterprise Data Discovery and Democratization  
  2. Process Automation and Efficiency
  3. Personalized Customer Experiences
  4. Contextual Search  
  5. Risk Management  

In the following sections, Mosaic will share shortened success stories from client engagements and how they tie to our top LLM business applications.

Top LLM Business Applications graphic showing Mosaic's top 5 ways businesses can harness LLMs

1. Enterprise Data Discovery and Democratization

Unlock the hidden insights buried within your vast data repositories by leveraging an LLM’s ability to extract meaningful patterns and connections. Empower your employees to access, analyze, and utilize data effectively, driving informed decision-making across the enterprise.

Mosaic’s Energy Customer: Enabling Contextual Search and Data-Driven Insights

Mosaic’s energy customer faced a challenge in efficiently retrieving relevant information from a vast repository of millions of unstructured images and documents related to geological sites. To address this challenge, Mosaic developed a state-of-the-art contextual search engine that empowers geoscientists to quickly uncover valuable insights from this extensive dataset.

Key Highlights: 

  • Data Democratization: The contextual search engine democratizes data access, providing geoscientists with a user-friendly interface to navigate and analyze millions of documents and images, fostering self-service data exploration and discovery.
  • Contextual Search: The search engine leverages advanced natural language processing (NLP) and computer vision (CV) techniques to extract meaningful information from unstructured data, enabling geoscientists to refine their searches based on specific keywords, filters, and precomputed attributes.
  • Geosentiment Analysis: The engine incorporates geosentiment analysis, derived from ML techniques and the customer’s internal geoscience knowledge, allowing users to gauge positive or negative sentiments associated with specific sites, providing valuable insights for lead generation.
  • Geolocation: The search engine integrates geolocation capabilities, enabling users to filter documents and images based on their geographical location, pinpointing relevant information to specific regions or sites.
  • Image Similarity Search: The engine utilizes a deep learning model for image similarity search, allowing users to identify and explore visually similar images, potentially uncovering overlooked connections and patterns within the dataset.


Mosaic’s contextual search engine has revolutionized the way the energy company’s geoscientists interact with their data. By enabling contextual search, data democratization, and advanced analytics, the engine has significantly reduced search times, improved data accessibility, and fostered data-driven decision-making, providing the company with a competitive edge in the energy sector.

2. Process Automation and Efficiency

Streamline repetitive and time-consuming tasks by employing LLM-powered automation. Automate processes such as data entry, report generation, and customer support interactions, freeing up valuable human resources to focus on higher-value strategic initiatives.

Mosaic’s Hospital Customer: Automating Purchase Order Exception Management  

The sheer volume of purchase orders (POs) processed by a large hospital system’s Supply Chain department made it difficult for staff to manually review PO confirmations for exceptions, leading to missed exceptions and downstream issues that could negatively impact patient care and the hospital’s bottom line. To address this challenge, the hospital sought Mosaic, with expertise in Natural Language Processing (NLP), text analytics, and machine learning to develop a tool that could automatically flag emails requiring attention.

Key Highlights: 

  • Process Automation: The model accurately flagged 99% of emails requiring attention, reducing the risk of missed exceptions, freeing up Supply Chain staff to work on other tasks.
  • Reducing Human Error: Machines do not suffer from fatigue the same way humans do over tedious tasks, such as reviewing 100’s of emails each day to look for specific information.
  • Layering Additional ML: Beyond being able to process all of these emails, additional features included the deployment of a classification ML algorithm to predict if an email requires further review.
  • Deployment: The hospital did not require a new system, so Mosaic built the tool to be integrated into software the users were already familiar with, letting the users to hit the ground running with their new AI.  


Mosaic’s tool not only provides a reduction in time spent evaluating PO confirmations, but also eliminates almost all the missed exceptions due to human error in reviewing thousands of purchase orders on a weekly basis, resulting in several beneficial downstream financial and patient experience effects.

3. Personalized Customer Experiences 

Enhance customer engagement and satisfaction by tailoring experiences to individual preferences and behaviors. Utilize LLMs to analyze customer data and interactions, enabling you to deliver personalized recommendations, targeted marketing campaigns, and proactive customer support.

Mosaic Helps Utility Company Extract Sentiment to Improve Customer Experience  

A leading retail energy company sought to extract valuable insights from its vast repository of customer call transcripts to improve customer experience and reduce churn. Mosaic employed topic modeling and deep learning techniques, including large transformer models, to analyze the unstructured call data and identify key topics, extract semantic meaning, and predict churn risk.

Key Highlights: 

  • Topic Modeling: Mosaic applied topic modeling to identify recurring themes and topics within customer interactions, gaining a deeper understanding of customer concerns and needs.
  • Deep Learning/Transformer Model: Mosaic utilized deep learning models like BERT to convert call transcripts into numerical representations, capturing the semantic context of each conversation.
  • Churn Prediction: Mosaic developed classification models using the extracted features from topic modeling and deep learning, enabling the prediction of customer churn with high accuracy.
  • Test-n-Learn (A/B Testing): Mosaic designed an A/B testing experiment to evaluate the effectiveness of intervention strategies in reducing churn among high-risk customers identified through the NLP models.


The NLP models enabled the energy company to personalize customer interactions, addressing specific customer needs and concerns. The ability to predict churn risk allowed the company to proactively engage with at-risk customers, reducing churn by an estimated 23%.

4. Contextual Search 

Contextual search represents a significant advancement in search technology, leveraging LLM capabilities to provide users with more relevant and personalized search results. By understanding the context of a user’s query, contextual search goes beyond traditional keyword matching, considering factors such as the user’s search history, location, and intent. This nuanced approach delivers more relevant results, improving user satisfaction and task completion rates.

Mosaic Delivers Voice Search Solution for Manufacturing Firm 

A global industrial manufacturing firm sought to enhance customer experience by developing a voice-enabled digital assistant that could effectively search and retrieve information from its extensive technical manuals. Mosaic Data Science leveraged deep learning and advanced NLP techniques, including transformer models and embedding-based indices, to create a custom AI-powered voice search solution tailored to the customer’s specific needs.


  • Phase 1: Document Extraction and Metadata Enrichment: Mosaic’s data scientists employed cloud OCR tools and NLP techniques to extract content from technical documents and operation manuals, adding contextual metadata to enhance searchability.
  • Phase 2: Indexing and Embedding: The extracted data was indexed using a full-text search engine, and state-of-the-art transformer models were trained to generate vector representations (embeddings) of words and phrases, enabling semantic search and improved relevance.
  • Phase 3: Search Relevancy Optimization: Mosaic developed a custom search relevancy function that utilized keyword and embedding-based indices, contextual information, and a gold standard set of questions and answers to rank search results effectively.


The AI-powered voice search solution enabled customers to quickly and accurately find relevant information from technical manuals, enhancing their overall experience and satisfaction. The solution saved countless hours for customers and internal teams by streamlining the search process and reducing the time spent manually searching through lengthy documents. It also provided a unique competitive advantage for the manufacturing firm, differentiating it from competitors and solidifying its position in the industry.

5. Risk Management 

In today’s complex and ever-evolving business landscape, effectively managing risk is crucial for success. LLMs are emerging as powerful tools that offer innovative solutions for diverse risk management challenges. With their ability to process vast amounts of data and identify hidden patterns, LLMs can significantly enhance risk identification, assessment, and mitigation strategies.

Mosaic Boosts Recovery Audit Firm Operations  

A leading recovery audit and contract compliance firm needed to increase efficiency and accuracy in searching millions of emails and contractual documents for critical information. Manually extracting specific contract terms, offers, and negotiations was time-consuming, error-prone, and costly.

Anticipated Solution:  

Mosaic is developing a prototype tool based on our Neural Search Engine LLMs and conventional search to automate the information extraction process. This initial phase focused on email communications, allowing auditors to make natural language requests for extracting and aggregating information.

Anticipated Results: 

  • Reduced Audit Time: The Neural Search Engine significantly reduced the time required to locate and extract critical information, allowing auditors to be more efficient.
  • Enhanced Accuracy: AI-driven approach focused searches on vital details, excluding noise and ensuring a more thorough audit process.
  • Increased Cost-Efficiency: Reduced operational overhead and improved productivity resulted in lower audit recovery costs and higher profit margins.
  • Unlocked Hidden Value: The solution identified unclaimed rebates and pricing opportunities by efficiently extracting critical contract terms and communications, maximizing potential revenue recovery.

Project Ongoing:  

Mosaic will continue to collaborate with the client to scope and execute subsequent phases, scaling up the capability to handle more diverse queries, emails, and other contractual documents. 

Top LLM Business Applications: Your Journey Starts Here

In conclusion, AI and LLMs are not just a technological leap but a strategic imperative. By embracing this evolution, businesses gain a distinct advantage—staying ahead of the competition, enhancing stakeholder experiences, and optimizing both time and costs.

Discover how our custom AI solutions can propel your business forward. The future belongs to those who harness the potential of AI today.

Ready to embark on your AI journey with LLMs? Contact us for a personalized consultation to find your Top LLM Business Applications.