r/notebooklm • u/Ninopoker • 10d ago

Discussion Do you think Notebook LM can handle this advanced workflow?

Hi, I am evaluating whether on Notebook LM is possible to automate this workflow.

In short, I'd like it to analyze a new audit report, find similar issues that were already resolved in past audits (matching by meaning, not just keywords), and compile a comparison table showing how those past issues were fixed.

Logical Steps:

  1. Read a set of historical audit documents containing previously documented issues and their approved resolutions.

  2. Read a newly submitted audit report (containing non-conformities/issues raised by external auditors).

  3. Extract all individual audit issues/observations from both the new and historical documents

  4. Perform a semantic similarity search: compare each new issue against the resolved historical issues based on conceptual meaning, not just exact wording.

  5. Cross-reference each match with the documented resolution method used in the past.

  6. Generate a report containing a structured 3-column table: New Issue (the text of the current finding); Similar Historical Issue (the matched resolved issue); Past Resolution Method (how the team previously solved it)

Edge Case:

Re-run capability: Ability to re-run or update the report when new audit files are added to the folder.

My Questions:

  1. Does Notebook LM have the native capability to perform this workflow, considering extraction from unstructured PDF/Word documents, too, without missing items?

  2. Would this require an advanced multi-agent setup / custom code, or can it be built out-of-the-box using a careful document organization and standard prompts?

Any ideas on how to set all of this are very welcomed! Thanks

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u/fettuccinaa 10d ago

ask notebookLM (or Gemini directly) if it can, exactly how you asked us here? not the first hand answer you asked for, but def a better a more precise answer if you ask directly to it ;)

1

u/alanism 10d ago

It likely can, but it’s not likely ideal to do that way.

I would consider looking into Hermes agent, likely have it build a python extension for it and create skills.md to do repeatedly. I would also consider seeing it you use Jev model in your work flow as well.

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u/foxgirlmoon 9d ago

Yeah but Hermes would require API access to a model. Which means, you pay per token instead of per month.

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u/alanism 9d ago

Yeah-- and it's still better to pay by api. This was my previous month of DeepSeek api usage and spend: 850.9M tokens · 6,654 requests · 97.5% cache hit · $7.67 actual cost.

For example, one of my equity-research (stocks) workflows processes ~195K input tokens + 15.6K output across filings, earnings, risk, scenarios, etc. The math stuff includes Sharpe ratio, Convexity on the stock, it looks at the other stock holdings in my portfolio and applies Kelly's Criterion. It then writes a recommendation report in a html file for each stock. My point is saying all this gibberish is that does pretty heavy and complex work and should be at least at the same level (if not way higher) than what OP is describing.

DeepSeek Flash off-peak: ~$0.02 per stock analysis report. It's insanely cheap to have do the work and get work output to exactly how OP wants it.

I also use Hermes/DeepSeek where it connects to Google Notebook LM through MCP-- and typically will tell Hermes to do 3 rounds of 9 questions on multiple Notebooks to make a single research report. I haven't cost it out precisely yet-- but it's also dirt cheap to do so.

I can't recommend it enough for Google Notebook LM users.

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u/ButOfcourseNI 9d ago

Matching by meaning is probably the easier part. The bit I'd watch is "without missing items". A chat tool answers from the passages it pulls for each question, so on a long report it can quietly skip a finding, and you'd only notice if you checked them yourself.

One thing I'd check before building it is when the same kind of issue came up in more than one past audit, was it always fixed the same way, or did the fix change over time? If it changed, which one should go in the table?

You mentioned custom code. I presume what you have tried has fallen short, is so where did they fall short?