Brief.AI is an innovative platform tailored to hedge funds and investment banks, revolutionizing insights into earnings calls by harnessing large language models.
Our platform aims to be the voice for any executive or analyst on the buy side or sell-side trying to analyze earning call transcripts through two products:
💬 Javi - Question Answering over Earnings Call Transcript
- The intelligent chatbot can engage in real-time queries regarding specific details from earnings call transcripts. This elevates user experience, ensuring immediate access to critical information without manual data trawling.
- This model efficiently extracts crucial performance indicators and financial metrics from a comprehensive collection of earnings call transcripts.
Our chatbot amplifies the functionality of large language models, empowering users to engage in interactive conversations with earnings calls. This versatile tool serves multiple purposes, such as:
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🤖 Comparison across multiple documents
- The chatbot uses an agent to compare queries that retrieves multiple documents and is able to create a chain of thought reasoning chain to answer queries.
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🧠 Memory:
- Memory refers to persisting state between calls of a large language model. You can continue to ask follow-up questions from initial queries without restating the context.
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⚡ Punctual Information:
- The chatbot provides quick and precise responses to specific questions, making it ideal for extracting timely information from earnings calls.
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🚨 Sentiment Analysis:
- Users can gauge the sentiment and emotional tone of earnings calls, helping them make more informed investment decisions.
📃 Detailed Earnings Calls Analysis:
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📚 Concise answers
- Utilizing cutting-edge language models, our system delivers succinct, structured answers extracted from verbose earnings call transcripts, streamlining the distillation of key performance indicators (KPIs) for analysts and executives.
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🧐 Effective KPI extraction from long transcripts
- Extracting data from unstructured sources like PDFs has become crucial for businesses, researchers, and individuals. Traditional manual methods are slow and error-prone, necessitating more efficient alternatives.
For more detailed information on these capabilities and concepts, please refer to our comprehensive product documentation.
For a complete guide to the documentation, please follow the steps outlined below to navigate through the GitHub organization:-
Javi-The-Earnings-Call-Expert: Chatbot powered by langchain.
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LongShort-Dataset: This is the dataset utilized for fine-tuning.
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LongShort: Fine-tuned script for models designed for KPI (Key Performance Indicators) extraction from earnings call transcripts.
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LongShort-Mistral-7B: Our model card for fine-tuned version of Mistral-7B.
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LongShort-Dolly-2-7B: Our model card for fine-tuned version of Dolly-2-7B.
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LongShort-Llama-2-7B: Our model card for fine-tuned version of Llama-2-7B.
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LongShort-Llama-2-13B: Our model card for fine-tuned version of Llama-2-13B.
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LongShort-Falcon-7B: Our model card for fine-tuned version of Falcon-7B.
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Website: Platform's UI/UX.
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Branding: Repository containing branding documentation and assets.
- Javi-The-Earnings-Call-Expert: Chatbot powered by langchain.