Top 10 ways businesses leverage Large Language Models (with case studies)

Today, we have a rapidly evolving technological landscape, where it is crucial for businesses to establish clear objectives before leveraging Large Language Models (LLMs). Having the right goals ensures that the implementation of LLMs aligns with any company's overall strategy and maximises potential benefits.
Over the next 5 to 10 years, artificial intelligence will transform all businesses. Those that continue to operate manually risk falling behind, missing out on the efficiency and innovation that AI offers.
To illustrate the impact of LLMs, we have identified the top 10 ways businesses use, leverage, and benefit from these models. Each method is supported by real-world case studies from our archives, demonstrating the practical applications and advantages of LLMs in various industries.
This exploration not only highlights the versatility of LLMs but also underscores their significance in driving business success in the coming decade.

1. Answer Generation

Large Language Models excel at generating precise and contextually accurate answers to user queries. This capability makes them invaluable for customer support and information services. By understanding the nuances of human language, LLMs can provide relevant information quickly and efficiently.
Businesses can use LLMs to automate responses to common customer questions, reducing the need for human intervention and improving response times. This not only enhances customer satisfaction but also allows employees to focus on more complex issues, leading to overall increased productivity.

Case Study: LLM-powered Semantic Search for a Marketing Research Business

Brainpool designed a Semantic Search system for a client's market research platform, allowing it to instantly find relevant information within vast amounts of historical data and across various document types. This system was designed throughout the AIScoping Programme.
Brainpool's data engineering experts are now supporting the client's team in implementing this AI capability within their proprietary marketing platform. This integration enables the client to efficiently find, access and utilise critical data, enhancing the platform's overall functionality and value.

2. Information Finder

Large Language Models are highly effective at locating specific information within large datasets, making them invaluable in research-intensive fields where quick and accurate data retrieval is crucial. Businesses can use LLMs to search through vast amounts of text, from reports to emails, to find relevant information swiftly and accurately.
This capability not only saves time but also enhances the precision of data analysis. By leveraging LLMs as information finders, companies can streamline their research processes, make informed decisions faster, and maintain a competitive edge in their markets. This leads to more efficient operations and better utilisation of resources.

Case Study: Information Extraction using LLMs for a Big 4 Accountancy Firm

Natural Language Processing can extract information from various documents such as Word, Excel, PPT, Emails, and PDFs, maximising work efficiency and document processing speed. We designed a strategy for developing an NLP platform for the forensics department of one of the top four accounting firms (name remains confidential).
This platform was designed to help the department efficiently process and analyse large volumes of documents, enhancing their ability to uncover critical information quickly.

3. Content Generation

Large Language Models are powerful tools for generating high-quality content quickly and efficiently. Businesses use LLMs to draft articles, blog posts, marketing copy, and social media updates, ensuring consistent and engaging communication. These models can mimic various writing styles and tones, making them adaptable to different brand voices and audiences.
By automating content creation, companies save time and resources, allowing human writers to focus on more strategic and creative tasks. The use of LLMs in content generation not only enhances productivity but also helps maintain a steady flow of fresh and relevant content, keeping audiences engaged and informed.

Case Study: LLM for Automated Press Release Generation for a Life Sciences Company

Our client’s team currently spends 3-4 hours daily manually researching articles and writing press release content for their clients in the Life Sciences sector. Brainpool designed an LLM-based system that automates this content production, generating press releases based on domain-specific data uploaded for each client account.
This advanced tool is estimated to reduce the time spent on manual content production by 50%, significantly improving efficiency. By automating routine tasks, AI is set to help the team to focus on more strategic and creative activities, enhancing the effectiveness of the  content creation process.

4. Understanding Your Customers

Large Language Models help businesses gain deeper insights into their customers by analysing vast amounts of data from various sources such as social media, reviews, and customer feedback. These models can identify trends, preferences, and sentiments, enabling companies to understand their customers' needs and behaviours better.
By leveraging LLMs, businesses can personalise their marketing strategies, improve customer service, and develop products that resonate with their audience. This enhanced understanding leads to stronger customer relationships, increased satisfaction, and ultimately, higher customer retention and loyalty.

Case Study: LLM for Customer Services Automation in Home Appliance Repair

Brainpool designed an automated customer service call centre report processing system for a UK-based home appliance repair service using Large Language Models. Our AI experts developed an LLM-based system that detects which part of a home appliance, such as a washing machine, is broken based on the call centre report. This AI-powered analysis can then enable  engineers to bring the correct part to fix the appliance on the first visit, reducing repeat visits and improving service efficiency.
The implementation of LLMs improved the accuracy of the client's predictions from 50% to 80%, significantly enhancing operational efficiency

5. Automating Repetitive Tasks

Large Language Models excel at automating repetitive and mundane tasks, freeing up human employees to focus on more complex and strategic activities. These tasks can include data entry, document processing, and routine customer inquiries. By automating these functions, businesses can significantly reduce errors and increase efficiency.
LLMs can handle large volumes of work consistently and accurately, ensuring that routine tasks are completed swiftly. This not only saves time and resources but also enhances overall productivity. The automation of repetitive tasks enables employees to contribute to higher-value work, driving innovation and growth within the company.

Case Study: AI-powered Timber Design Software for Staircraft, UK's Largest Timber Manufacturer

Brainpool partnered with the Staircraft Group, the largest timber floor and stair manufacturer in the UK, to develop an automated, AI-powered timber design tool called DAISY AI. Staircraft faced a bottleneck in their fast-moving sales and complex design process due to high demand and a limited number of designers. On a good day, an experienced designer could produce 2-3 designs, but this was insufficient to meet demand, leading to lost opportunities and revenue.
Increasing the design team was impractical due to talent shortages and inefficiencies. Human designers, while effective, were not always efficient, resulting in wasted materials and inflated costs. To overcome these challenges, Staircraft combined their construction expertise with Brainpool’s AI expertise to create DAISY AI, an AI-powered timber design software that enhances productivity, efficiency, and scalability.

6. Data-Driven Recommendations

Large Language Models can analyse vast amounts of data to provide personalised recommendations, making them invaluable for businesses in e-commerce, streaming services, and other industries. By understanding user behaviour and preferences, LLMs can suggest products, content, or services tailored to individual needs.
This personalisation enhances user experience, increases engagement, and drives sales. Businesses can leverage LLMs to offer data-driven recommendations that keep customers satisfied and loyal. This not only improves customer satisfaction but also helps companies stay competitive by delivering more relevant and timely suggestions, ultimately boosting revenue and growth.

Case Study: Visibility of Purchases’ Impact On Personal Carbon Footprint for Creed Partners

A green fintech disruptor, Creed Partners, needed to track and quantify people's personal carbon footprints. The idea was to enable purchasers of their solutions to know the CO2 emissions of each purchase, and thus make environmentally conscious decisions. Creed aimed to validate the concept's feasibility and eventually lead in the fintech space.
The project involved several challenges: securing access to customer transaction data, obtaining reliable data on the carbon footprint of various products and services, using this data to generate personalised carbon footprints, and creating a mechanism to classify transactions automatically. Overcoming these challenges was vital for Creed's functionality. CEO Roshan George partnered with Brainpool’s AI experts in machine learning and data engineering to bring the application to life.

7. Demand Forecasting

Large Language Models are highly effective tools for demand forecasting, enabling businesses to predict future trends and customer needs accurately. By analysing historical data and identifying patterns, LLMs can forecast demand for products and services, helping companies manage inventory, optimise supply chains, and plan marketing strategies. This predictive capability allows businesses to reduce costs, minimise waste, and ensure they meet customer demand efficiently.
Additionally, LLMs can account for external factors such as market shifts and seasonal trends, providing a more comprehensive and dynamic forecast. Using LLMs for demand forecasting enhances operational efficiency and provides a competitive edge by enabling proactive decision-making and better resource allocation.

Case Study: Demand Forecasting with Temporal Fusion Transformer for a US-based Restaurant Chain

Temporal Fusion Transformer (TFT) models are used to predict item-level demand with high accuracy, ensuring stock and operational resources are accurately measured and planned according to predicted demand. For a US-based restaurant chain, we implemented TFT models and achieved a high accuracy level with less than 10% MAPE (Mean Absolute Percentage Error) in demand predictions.
This precise forecasting allows the restaurant chains to manage inventory and resources efficiently, reducing waste and ensuring they meet customer demand effectively. The enhanced accuracy provided by TFT models supports better decision-making, optimize resources and achieve cost-efficiencies at scale. .

8. Design and Content Creation

Large Language Models can greatly enhance design and content creation processes. They assist designers by generating ideas, drafting initial designs, and creating detailed artworks based on specific inputs. Additionally, LLMs can produce written content such as articles, marketing materials, and social media posts, ensuring both consistency and creativity.
By automating these tasks, businesses save time and resources, allowing human creators to focus on more strategic and innovative projects. This integration of LLMs into design and content creation not only boosts productivity but also fosters creativity, ensuring a steady flow of high-quality content and designs. The ability to quickly produce and refine ideas helps businesses stay agile and competitive in dynamic markets.

Case Study: Automated AI-Driven Design Pipeline in E-Commerce for Crown & Paw

Crown & Paw is an e-commerce platform specialising in high-quality custom pet portraits and products, delighting thousands of pet owners. However, their design process was complex and time-consuming, involving various systems and stakeholders. To enhance their design and content creation, Crown & Paw partnered with Brainpool to develop an AI-powered design pipeline.
This solution improved design speed and reduced turnaround times, allowing faster product delivery. It also helped accommodate high demand during peak periods without limiting marketing activities. By streamlining the design process, Crown & Paw avoided the linear costs of hiring more freelance designers, enabling scalable growth and exploring new product opportunities and revenue streams.

9. Video and Image Analysis

Large Language Models are highly effective in analysing video and image content, making them valuable tools for businesses in media, security, and marketing. They can automatically tag and categorise images, interpret video content, and generate detailed visual summaries. This capability allows companies to manage and utilise visual data more efficiently.
By leveraging LLMs for video and image analysis, businesses can enhance their content management systems, improve security monitoring, and create targeted marketing campaigns. The automation of visual data analysis not only saves time and resources but also increases accuracy and scalability in handling large volumes of visual content.

Case Study: Machine Vision System to Detect Electric Vehicles on European Motorways

The Brainpool team developed a machine vision system capable of identifying electric vehicles in large datasets of CCTV footage from cameras on European motorways. During the proof of concept, the system achieved higher-than-human accuracy in detecting electric vehicles by their number plates.
This advanced technology enables more efficient monitoring and analysis of motorway traffic, providing valuable data for infrastructure planning and optimization of placing electric vehicle charging stations.

10. Legal and Compliance Assistance

Large Language Models can significantly enhance the ability of authorities to ensure legal compliance by automating the review and analysis of vast amounts of legal documents. These models can detect regulatory breaches, monitor compliance with laws, and generate reports on compliance status. With their ability to analyse intricate legal details, they ensure thorough and precise evaluations.
By using LLMs, authorities can streamline their compliance monitoring processes, reduce the time and cost associated with manual reviews, and improve the accuracy of compliance assessments. This helps maintain adherence to regulations, better manage risks, and ensure that individuals and organisations comply with legal requirements.

Case Study: LLM for Parking Ticket Appeal Process Automation for a UK-based Client

A UK-based client sought our help to automate the manual and time-consuming process of reviewing and approving or rejecting parking ticket appeals. Our Brainpool team designed an automated bot to communicate with parking ticket holders, and advice advising them on local parking regulations in each of the 60 UK regions.
The bot was designed to make decisions on whether an appeal should be accepted or rejected based on a decision tree specific to each location. The objective was to streamline the appeal process, ensuring quicker and more accurate decisions, reducing the workload on human staff, and improving overall efficiency.

In Summary …

The potential for AI to enhance and streamline business processes is vast. Large Language Models (LLMs) offer transformative capabilities across various domains, from improving customer service to automating repetitive tasks. By fine-tuning LLMs to your specific business needs, you can achieve the accuracy required to make these AI solutions practical and effective.
The integration of LLMs can lead to significant improvements in efficiency, productivity, and innovation, ensuring that your business stays competitive in an increasingly digital world.
Furthermore, embracing AI technologies will not only help you stay ahead but also unlock new opportunities for growth and success.
If you're ready to explore how LLMs can revolutionise your business operations, reach out to us today to start your journey towards smarter, more efficient solutions. Let us guide you in harnessing the power of Large Language Models to transform your business processes and achieve your strategic goals.