> Monitor Apple, Google, Microsoft, and Meta stock. Notify me if any of them start trending toward being undervalued

If you actually had a system that could detect when a stock was "undervalued" you should just trade directly on that system instead of selling it to consumers. This is pretty clearly scammy/predatory towards retail investors.

We only look at when the stock is objectively "undervalued". I'm not saying the system will tell you that a stock like Palantir is undervalued because it has a bright future. No. This system only tells when a stock is objectively undervalued. There are a few ways to know this.

Here some examples:

- Market cap is less than book value.

- Market cap is less than free cash flow x 8

There are other ways, but these are some examples. Being undervalued doesn't mean its a good company, the trick is knowing why its undervalued and if that valuation is justified.

> the trick is knowing why its undervalued and if that valuation is justified.

If it’s justified, then it’s not undervalued.

Everything you described above is also just wrong and you should please stop encouraging uneducated retail investors to believe anything that fits these heuristics is “objectively undervalued”.

If any of these metrics were arbitrage, it would mean the fastest execution wins and the gap wouldnt last long. These metrics almost never work

> This system only tells when a stock is objectively undervalued. There are a few ways to know this.

> - Market cap is less than free cash flow x 8

Lol. "Objectively".

If that were true you wouldn’t need an ai to tell you.

Not necessarily. Say you can make 20% a year with your system. That's very respectable. But unless you have a large account already (1M?), you will make more by providing this knowledge to others.

You don’t need 1M to trade 1M. Ive seen retail accounts with 50x leverage

This looks like a scam.

If it looks like a duck and walks like a duck....

It's just a research and analysis tool that automates the process of reading lots of SEC Filings and earnings call transcripts and checking the news and stock quotes back to back.

Just automates the research that users would do manually.

What data do you collect about users, and are there any protections against taking trading ideas? Institutional traders would be wary of using the application, cautious of losing any edge by tipping their hands of what equities they are looking at to a third party.

If the application is meant for retail, how do you plan on funding the project? Answering this question would better illuminate the stakeholder's incentives and if they align with users' interests.

We have offerings for both retail and institutions. Institutions can choose between on-prem solutions or a dedicated cloud deployment.

Both retail and institutions can also use for our SAAS solution. We don't share our user data with third parties.

I do review the AI interactions for the following reasons:

- To ensure the AI system (AI assistants and agents) meets expectations.

- Safety: To ensure the AI system is not generating false or misleading information.

- To understand how the AI system is performing and how to improve it.

When you say, “monitor red flags” what is actually happening ?

How are you determining red flags ?

Will an LLM be running every x hours analyzing news, so I can give very specific things to look for ?

Red flags are things like significant drops in stock price, revenue, earnings, customer satisfaction, lawsuits, or changes in senior management.

You can specify the red flags, or the LLM will specify them for you don't include them.

You can also specify how often you want the LLM to monitor things for you.

Is chat really the best interface for a stock market analysis tool?

Locking this behind a signup form seems like a mistake.

I tend to agree. If you're dead set on locking behind a signup, at least the example queries shown (e.g. 'Summarize Apple's latest earnings' should be clickable so that users can see how it works.

Can it help with technical analysis as well? And screening of stocks based on technicals?

Not yet. I plan to see if we can offer value for technical analysis. We specialize in fundamental analysis.

You'd need to figure out an embedding for the seaweed.

Lol. Point & figure ;-)

I haven't really used agentic AI yet and I am already completely sick of it.

40 questions to Saturday just sounds ridiculous.

I feel like on this trajectory my broker is soon going to be pretending my trailing stop is an AI agent monitoring when to get out of the trade "in the background".

Is this investment advice?

> "Investment adviser" means any person who, for compensation, engages in the business of advising others, either directly or through publications or writings, as to the value of securities or as to the advisability of investing in, purchasing, or selling securities, or who, for compensation and as part of a regular business, issues or promulgates analyses or reports concerning securities...

https://www.govinfo.gov/content/pkg/COMPS-1878/pdf/COMPS-187...

Does it matter here?

> any person

The AI defense.

The person who made the tool is culpable. Same way if a lawyer hires an intern that preps legal documents is responsible.

However, governments in thw US love to whitewash liability so this is just academic.

Of course it matters! AI doesn't automatically absolve you from your legal responsibilities...

I'd bet there's a person somewhere that receives money in exchange for sharing the AI's analysis, which would fall squarely into the second half of the definition:

> [any person] who, for compensation and as part of a regular business, issues or promulgates analyses or reports concerning securities...

Is there any custom models or logic to this; or is this just a cron job wrapped around an LLM?

Capturing data, feeding it to an LLM, and hoping it actually does comparisons properly?

Is the LLM writing code that is being executed for each query or job?

Otherwise, all I am seeing here (and based on your comments saying "LLM") it just appears this grabs data, gives it to an LLM, and "magic output"

There is a lot of custom logic and proprietary data, including a custom LLM framework and an agentic workflow framework as well as an insight engine.

Eh... doesn't have data after October 2023.

The cutoff date for the data used to train the model is October 2023, but the AI Assistant can access historical, real-time market data, search, and browse the web. It's still not perfect, though.