"The Notion of Equity Research"
Hey, you successfully discovered PalmyAI. First and foremost, this service is in a beta state, meaning it's under active development.
Currently, the beta is not public, meaning you must be authenticated before accessing the workspace.
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The goal of PalmyAI is to create a fusion of NotebookLLM and BamSEC. Therefore, we started by building a document reader;
The document reader is all set up for: - Annotating SEC filings (1.8M**) and earnings call transcripts (250K**), e.g., with inline markings and comments. - Being autonomous: no document uploads, no SEC connection. - Team collaboration and document organization. - Speed*, as our compression reduces size by an average of 1,624%. - Intuitive navigation & search through exhibits, tables, and TOC. - Saving SEC tables so you can return to a table at any time. - Great visualization capabilities, e.g., plotting all 10-K tables.
PalmyAI is able to: - Understand the document structure precisely - Use the entire corpus to work with SEC tables, images and text sections. - Work with user annotations, if wanted, as context. - Cite the source(s); PalmyAI solely relies on first-tier sources. - Query person profiles, such as executives and directors. - Outperform NotebookLLM through design, simplification, cost efficiency, and dedicated ER infrastructure (namely, our specialized parsers & RAG).
Future Plans: - *Speed: Proximity support to outperform the SEC first-load for EU/Asia. - Quantity increase: PalmyAI currently covers 1,231,231 vectors — which is good for a beta, but not yet at the scale we aim for. - Focusing on PalmyAPI further, as PalmyAI enables generating custom datasets at scale. - ...
**As of 07/07 (That's the very least to start the beta with though)