As AI becomes essential in finance, Google’s NotebookLM stands out for offering an accessible way to summarize and organize financial documents. However, it lacks the depth, precision, and integration that finance professionals need.
In this article, we explore NotebookLM’s capabilities and limitations for investment analysis and show why the Hudson Labs Co-Analyst is better suited for investors. Save hours on manual uploads and data extraction with the Co-Analyst.
NotebookLM Overview
NotebookLM is an AI-powered notebook developed by Google, designed for research, summarization, and note-taking with AI-generated insights.
Core capabilities:
- Upload documents (e.g. SEC filings and research reports) for summarization and analysis.
- Generate audio overviews or podcasts, making dense financial documents more accessible.
- Includes presets for creating briefings, FAQs, and timelines.
Limitations of NotebookLM for Investors
- Manual uploads: Users must upload each document individually. While Google Drive is supported, NotebookLM can only access Google Docs and Slides from the Drive.
- No EDGAR or transcript integration: Cannot extract directly from EDGAR, no automated SEC filings analysis (e.g., NVDA 2024 10-K).
- Built on a generalist model: Gemini 2.0 is not designed for financial analysis and often returns imprecise or irrelevant outputs.
- Hallucinations: A common problem with generative AI, leading to false and/or misleading answers.
- Unstructured output: Generates text-heavy responses with limited tabular formatting, limiting further analysis.
Hudson Labs Co-Analyst: The Best AI tool for Analyzing SEC Filings and Call Transcripts
- Instant access to documents: Access SEC filings, earnings transcripts, press releases, and more for all US issuers and 1400+ ADRs in real-time—no uploads required.
- Finance-specific, numeric-focused: Unlike generalist AI, we specialize in extracting data from unstructured sources and eliminating generic, non-actionable responses.
- Tabular output by default: Investors prefer structured data. Our models format results in tables for easy analysis.
- Relevance ranking & noise suppression: Our AI prioritizes the most relevant financial information, reducing irrelevant or misleading outputs.
In comparison, NotebookLM’s dense, unstructured outputs are difficult to use for further analysis.
The Co-Analyst is Built for Institutional Equity Research
Hudson Labs Co-Analyst goes beyond summarization:
- Guidance extraction: Find recurring, one-time, numeric, and semi-quantitative guidance, delivering complete and structured outputs. This is an area where many AI models fail or provide highly inconsistent results. See more here and here..
- Cross-company comparison: Aligns KPIs across peers and time periods, supporting qualitative and quantitative analysis.
- Mathematical reasoning: Accurately handles financial metrics, including percentage changes and annualized calculations.
- Consistency & factuality: Unlike chatbots, the Co-Analyst outputs are consistent, factual, and complete.
Investors also use Hudson Labs to assess forensic risks in governance, related parties, and management integrity, surfacing downside risks beyond traditional keyword searches.
Sign up for a 14-day free trial today and transform your workflow for due diligence, idea screening, and portfolio risk monitoring.
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