that is going to require a lot of data and database management and offmarket deals are all case-by-case so it almost certainly wouldn't be easy to productize (i.e. you probably couldn't get AI to do this). 

Here you may find some old pictures, descriptions, and other pertinent property data. 

By prioritizing the data and broadening my search to different markets, I managed to achieve success.

You may think you know a lot about the data, but evaluating the actual house isn't the same. 

New investor here.
Thinking about end to end pipeline management for finding, closing, rehab, rent, hold/sell deals.
What tools are you using to keep your information organized, clean, reportable, etc?
Seems like t...

It's due to market data and inflation. 

The city's strong rental market driven by a growing population ensures a steady income stream and with affordability as well as a median home price below the national average, Cleveland stands out as an attractive option for those seeking a promising return.

Starbucks has the ability to select upcoming neighborhoods for their stores to be built due to the fact they have a team specifically for this reason by using demographic and property data , buying up these locations before home prices increase in value with the average home within a quarter mile of a Starbucks rises in property value by 96% don't quote me on this, I heard all of this from a YouTube video so I was wondering if any fellow real estate investors have any evidence that this theory is true so we all could piggy back off this by looking into future Starbucks stores being built?

What you need is data on what rates/costs/terms you can get on DSCR and then base your decision on real figures.  

Amit, John is right, that AirDNA is one of the best data points, but it should be taken into consideration with other input (first-hand knowledge on the ground, your own competitive analysis, etc.).That said, DM me the address and I'm happy to send you some info from my AirDNA account.