I found the argument(s) interesting although the animations hurt readability and clarity.

I've watched the area of commercialized remote sensing products with some interest, because I'm in the non-commercial remote sensing line.

The way NASA handles derived data products is (broadly) through "levels":

  L0: measurement, still in instrument native units (e.g., DN's)
  L1: calibrated and put into physical units (e.g., watts/cm2)
  L2: scientifically-useful product (surface reflectance at 450nm, CO2 concentration)
  L3: L2 that has been aggregated into a map, possibly also across time or instrument
  L4: data has been filtered through a time-stepped physics-based model

The lowest level that's commonly useful for applications is L2. A decent-sized satellite might have several L2 data products serving different user communities, e.g., CO2 concentration, methane concentration, and photosynthetic activity can all be recovered from remote-sensing spectroscopy, but they serve different uses.

One advantage of the above decomposition is that L2-L4 data can be validated with in-situ measurements. They are not just indexes -- they are targeted at a certain physically-measurable quantity.

This allows judgement whether the intermediate products (L2 CO2) are actually good, or improving. It also allows combining intermediate products from different sources (which is a hard problem). This is because both sources are trying to measure the same thing by design.

It is true that (for example) current spectroscopic remote sensing allows retrieval of a lot of L2 products for diverse communities -- scores of products, from mineral abundance to urban land use to agriculture to snow/ice to algae.

I do agree with OP that it will be impossible for any company to "cover the waterfront" of even half of these products. The measurement and each individual product take a lot of effort to get right.

But it also seems like there are commercial opportunities for some specific such products -- e.g., methane concentration/fluxes, or Evapotranspiration/soil moisture.

Wouldn't a subscription-based service to these products allow for continuous improvement of the underlying product, either through new measurements or through better algorithms?

So, in a nut, in the context of OP, what's the difference between:

-- an always-improving subscription-based "vertical service" for a L2 product like I just described,

vs.

-- a "problem-solving application" like the OP is advocating?