AWS Only
AI-Driven Competitive Analysis for Blue Light Card
Blue Light Card faced challenges with a manual, time-consuming process for onboarding new data sources and scaling their competitive analysis. Firemind, leveraging AWS technologies, created an AI-powered solution to automate content extraction and analysis using a Retrieval-Augmented Generation (RAG) approach.
AWS ONLY ·
AI-Driven Competitive Analysis for Blue Light Card
Blue Light Card faced challenges with a manual, time-consuming process for onboarding new data sources and scaling their competitive analysis. Firemind, leveraging AWS technologies, created an AI-powered solution to automate content extraction and analysis using a Retrieval-Augmented Generation (RAG) approach.
At a glance
Blue Light Card offers exclusive discounts and benefits to over 2 million emergency service workers, NHS staff, and other frontline professionals in the UK, helping them save on various purchases from leading brands across multiple sectors.
Challenge
Blue Light Card's main challenge was the manual and labour-intensive process of scraping and analysing competitor data, which limited their ability to scale and adapt quickly when data sources or website content changed.
Solution
Firemind developed an AI-powered solution using AWS technologies to automate data ingestion, content extraction, and competitive analysis. The system leverages a Retrieval-Augmented Generation (RAG) approach, enabling scalable, efficient analysis while reducing manual effort and improving adaptability.
Services used
Firemind's PULSE
Amazon S3
Amazon Bedrock
AWS Lambda
Outcomes
100% reduction in manual data processing.
50% increase in scalability without adding additional full-time employees (FTEs).
Business challenges
Manual data processing limits scalability and efficiency
Blue Light Card faced significant challenges in their competitive analysis processes due to a reliance on manual data scraping and analysis. The team had to manually select and extract relevant content from competitor websites, a time-consuming task that required substantial human effort. This approach was not only labour-intensive but also prone to errors, particularly when website content changed unexpectedly, causing disruptions in data consistency and reliability.
Additionally, the manual process severely limited Blue Light Card’s ability to scale their operations. As the demand for more comprehensive and timely competitor analysis grew, the existing process became a bottleneck, restricting their capacity to analyse additional data sources or expand their scope without increasing full-time employee hours. The need for a more efficient, scalable solution was clear to enable Blue Light Card to remain competitive and responsive in a fast-paced market.
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Solution
AI-powered automation enhances data processing and scalability
To tackle Blue Light Card’s data processing challenges, we developed an AI-driven solution leveraging several key AWS services. Amazon S3 was used for scalable and secure storage of both raw and processed data. This ensured that large volumes of data could be easily ingested and managed without constraints.
We integrated Amazon Kendra to perform intelligent semantic search and web scraping. Kendra’s advanced search capabilities allowed for efficient extraction and indexing of relevant competitor data from various web sources. This setup not only automated the content retrieval process but also enhanced the accuracy of data extraction, addressing issues caused by dynamic website content.
AWS Lambda was employed to handle serverless computing tasks, enabling real-time processing of incoming data and triggering workflows without the need for dedicated infrastructure. This approach streamlined the backend operations and improved system efficiency.
Finally, Amazon Bedrock was utilised to deploy Anthropic large language models (LLMs) that implemented a Retrieval-Augmented Generation (RAG) approach. This integration allowed the system to generate actionable insights and conduct in-depth analysis of competitor data. By combining these technologies, we created a scalable, automated solution that significantly reduced manual efforts and improved the agility of Blue Light Card’s competitive analysis process.
Reduced manual processing efforts
The project achieved a significant reduction in manual processing efforts, cutting down the time and resources required for data scraping and analysis by 100%. This automation not only streamlined the workflow but also minimised human errors, leading to more reliable and consistent data insights.
Enhanced scalability
Scalability was notably enhanced, with the system allowing Blue Light Card to expand their competitive analysis capabilities by 50% without increasing full-time employee hours. The new solution efficiently handled larger volumes of data and additional competitors, providing the flexibility needed to adapt to market changes and growth.
Model Spotlight
Claude Instant V1
We chose Claude Instant V1 for its efficient and real-time processing capabilities, which are crucial for applications requiring rapid responses. This model excels in delivering fast and accurate results, making it ideal for scenarios where speed and responsiveness are essential.
Claude V2:1
Claude V2:1 was selected for its advanced understanding and contextual capabilities, which are vital for more complex interactions. This model offers enhanced comprehension and nuanced responses, making it perfect for handling intricate tasks and providing in-depth assistance.
Why Firemind
As a specialised AWS partner with experience across diverse industries and high-profile customers, Firemind demonstrated a deep understanding of how to implement advanced machine learning and generative AI solutions effectively. Their capability to deliver tailored solutions, combined with their reputation for excellence in AWS infrastructure, made them a trusted partner to address Blue Light Card's unique challenges in data processing and competitive analysis.
100%
Reduction in Manual Data Processing
The automated solution eliminated the need for manual data scraping and analysis, significantly reducing time and effort.
50%
Scalability increase
The AI-driven system enabled Blue Light Card to scale their competitive analysis operations by 50% without adding additional full-time employees (FTEs).
Added value
The AI-driven system provided Blue Light Card with deeper insights and more accurate data, enabling them to make informed, data-driven decisions. With the ability to rapidly process and analyse competitor information, Blue Light Card could quickly adapt to market trends and stay ahead of the competition.
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