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Case Study — 13 May, 2024
Highlights
THE CLIENT: A global professional services company
Generative Artificial Intelligence (AI) refers to AI models that generate new content that can represent a range of media, including text, video, code, audio or synthetic data. The first examples were Large Language Models (LLMs) that consume immense amounts of data, making them capable of understanding and generating natural language and other types of content. Capabilities continue to evolve to encompass a wider array of outputs.
This technology is accelerating how many businesses operate today to support existing clients and target new opportunities. This is especially important in the professional services industry, where efficiently analyzing data to quickly uncover actionable insights has become paramount to creating a competitive edge.
This professional services firm was tasked with finding a way to leverage generative AI to help staff members save time locating and analyzing large amounts of data to support client growth plans. The team decided to build a model leveraging generative AI and load it with useful data to assess a wide range of industries, companies and specific topics.
Pain Points
The team planned to leverage generative AI within an internal model to help staff members quickly surface valuable insights. To do this, they needed to aggregate, parse and structure data in the model to make it LLM friendly and create appropriate prompts to query the data. In particular, they wanted to gain access to comprehensive company filings and use this to:
The team reached out to S&P Global Market Intelligence ("Market Intelligence") to see what data was available.
The Solution
Specialists from Market Intelligence mentioned that the company had won several awards for AI and LLM capabilities,1 including emerging top in WatersTechnology 2023 ranking of the best AI technology providers. They then discussed the Global Machine Readable Filings offering that would provide the team with the ability to:
Gain access to aggregatedand parsed information |
The Global Machine Readable Filings dataset provides parsed text for global annual and interim reports, broken into the various sections identified by a company, with extraneous information such as page numbers, images and tables removed. This enables users to perform Natural Language Processing (NLP) on an entity's filings over time to monitor strategic Initiatives, M&A plans, new product launches, ESG efforts and more. The dataset covers 90K+ entities and includes:
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Efficiently deliver data to the model |
Delivery via Snowflake's cloud-based platform eliminates the data ingestion process and significantly improves productivity and efficiency for data access. Snowflake's unique cloud-based architecture enables near-infinite scalability for faster queries at lower costs, delivering live, ready-to-query datasets that are always up-to-date and do not require transformation. |
Key Benefits
Members of the organization were looking for filings data and were delighted to see that Market Intelligence had already embraced AI and was offering filings in a machine-readable format, which would enable them to spend more time on higher-value activities. The team subscribed to the dataset and are now able to:
[1] A-Team's 2019 Data Management Insight Award for Best Proposition for AI, Machine Learning, Data Science, and the 2020 Data Management Insight Award for Best Proposition for AI and Machine Learning.
Case Study