Using AI to Extract Insights from Web-Based Public Information
In the fast-paced world of asset and LP/GP due diligence, web-based information has become an essential complement to traditional proprietary data. Market research, trend analysis, and risk assessment increasingly rely on the vast amount of online data available. Publicly accessible web-based information, particularly alternative data sources like customer reviews, social media, and blogs, is proving invaluable by offering unique insights.
However, efficiently extracting and synthesizing this information presents a significant challenge. There are three main hurdles to consider:
Identifying Relevant Sources: Finding the right page or website to gather information from amidst the vast sea of data is increasingly difficult. Even with the aid of search engines like Google, identifying the most pertinent pages requires screening through numerous options, which is time-consuming.
Handling Unstructured Data: Web-based data often comes in various formats—blogs, reports, news articles, company websites, etc.—making it difficult to read, digest, and interpret consistently. This complexity can lead to critical insights being overlooked.
Synthesizing Insights: Once the information is gathered, synthesizing the extensive inputs into a coherent insight while ensuring references to the original sources for validation is another time-intensive task.
Recent advancements in generative AI technology, such as ChatGPT and Anthropic, offer powerful solutions to these challenges:
Automated Source Identification: AI can scan and analyze a far greater number of web pages than a human can, determining their relevance to the specific topic or question at hand. AI can even utilize search engines like Google to compile a list of the most relevant pages, addressing the first challenge effectively.
Structuring Unstructured Data: AI technologies excel at interpreting unstructured data across various formats, from blogs and news articles to Reddit threads and customer reviews. This capability directly addresses the second challenge by ensuring that no valuable insights are missed due to format variations.
Generating Uniform Outputs: AI can synthesize information from multiple documents, organizing and connecting the key insights into a uniform output. It also provides clear references to the sources of these insights, tackling the third challenge by making the information easy to validate.
The AIx2 software offers an optimized solution for funds and financial institutions by enhancing web-based information searches. Notably, AIx2 allows for the seamless integration of web-based data with proprietary data (e.g., virtual data rooms). By combining insights from both sources, AIx2 delivers the most comprehensive answers while providing detailed source references for easy validation.
Funds using the AIx2 software report nearly 90% time savings in their web-based information analysis, with improved insights. These benefits are particularly evident in applications like due diligence and market trend analysis. The Amazon due diligence case study below illustrates this time-saving advantage. For more details, you can request the full case study using the contact form on the AIx2.ai website.
We invite you to experience the transformative power of AIx2 in your fund processes. Whether your goal is to streamline operations, reduce costs, or enhance the quality of your insights, AIx2 is the solution you need.
Contact us today to see how our platform can revolutionize your due diligence process and help you make smarter, faster decisions.
