fluxode

Congrats on the launch! Just some friendly advice: financial documents such as quarterly earnings are actually highly structured via xrbl. If you are positioning the company as an unstructured -> structured process, then using these types of financial documents is probably not a great example even though everybody seems to do it.

Two questions:

1. How is this different from Syncthing and similar solutions? Syncthing is free, open-source, cloud agnostic and easy to use to accomplish what seems to be the same task as Moonglow. 2. What is serverless about this? It is not clear from the pitch above.

It appears a few features of the website do not work (tested on the latest MacOS and IOS). It seems that none of the links at the bottom of the page work and a few of the company icons do not load. I suggest you look into fixing these features and generally checking the functionality of the site as a whole.

Sorry to pile on, but this doesn't look great. Most people with any quantitative finance experience will tell you this is the wrong approach / the wrong application of these types of techniques. ML in trading is primarily used for portfolio optimization and relative value-type analysis. It (and especially Reinforcement Learning) are not useful if you a just trying to build signals to trade with. And Fibonacci Retracements are only kinda useful as a visual tool for assets that are mean-reverting in some capacity (i.e. forex). It is applicable to Crypto to an extent, but the volatility of Crypto nullifies most of the usefulness as this as an actual trading signal.

If you really want to pursue this, it would be helpful if you provided a bit of info on how the strategies worked, what type of hedging / risk management is going on, etc.

Best of luck