Features
AI Generated Summaries
Effortless Insights from Earnings Calls and Annual Reports
Overview
Navigate through Earnings Calls Transcripts & Annual Reports with AI-crafted summaries.
Key Benefits
- Enhanced Readability: The summaries present complex information from filings and transcripts in a concise and easily digestible format, enhancing readability and making it more efficient to grasp key insights without getting bogged down by extensive technical details.
- Grasp Key Takeaways: Key topics and areas are identified and separated within the AI-generated summaries, allowing you to quickly grasp the crucial takeaways and focus on the most pertinent information.
- Identify Changes from Past Disclosures: By comparing the current summaries with past disclosures, you can easily identify and track changes in a company’s risk factors, financial performance, or strategic outlook, facilitating better-informed decision-making.
How AI-Generated Summaries Work
- Summary-Generation: The LLMs are fed the long-form content of the filings, extracting relevant information and key points.
- Prompt-Based: Utilizing a predefined prompt, the the LLM organizes it into a structured and concise summary. This ensures that the most important details and insights from the documents are highlighted effectively.
How to Use AI-Generated Summaries
- Read the Long-Form Content: For a more in-depth understanding of the topic, please refer to the full transcripts and reports.
- Upcoming Features: a. Citations: In future versions, we will provide citations for each section, allowing you to easily refer to the original content. b. Custom Prompts: You will also have the ability to create and save your own prompts to generate personalized summaries based on your specific needs.
FAQs
Q: How accurate are the AI-generated summaries?
A: The AI-generated summaries are based on LLMs and are designed to summarize only based on the underlying transcripts/annual reports. However, we have observed that in rare cases, there is a possibility of hallucinations. We are actively working towards auto-identifying these from our end, but we request you to report any inaccuracies when found.