Collection
A daily batch pulls store charts, keyword suggestions, competitor install brackets, ratings and review histograms. Every record is tagged with a reliability grade, and low-grade data is never allowed to calibrate a forecast.
About
8bit is the mobile app studio of VRAVIO Inc., a corporation registered in the Commonwealth of Kentucky, United States. We design and publish small Android utilities.
Most people do not want another platform. They want a thing that converts a file, counts a number, or scans a code — and then gets out of the way. Those apps are unglamorous, and that is exactly why they are usually badly made: slow, ad-choked, or abandoned two updates after launch.
We treat that gap as an engineering problem rather than a creative one. Instead of guessing which app to make next, we built a system that reads the store every day — charts, keyword demand, ranking movements, competitor metrics, and the reviews where users say plainly what is missing. AI processes that volume and returns scored candidates with its reasoning attached; we then model whether a well-made version could sustain itself before anyone writes code.
Benchmarking tells us what already works. The teardown tells us where it fails. The forecast tells us whether fixing that is a business.
That is the whole difference between us and a copy factory. Benchmarking tells us what already works; the teardown tells us where it fails; the forecast tells us whether fixing that is a business. What ships is the same job done measurably better on the axis users complain about — not the same app with a different icon.
And because every launch feeds its real numbers back into the model, the studio gets better at predicting than it was the month before. That compounding is the asset. The apps are just what it produces.
The studio
Charts, keyword demand, ranking movement and review histograms land in one place. Candidates are scored there, forecasts run there, and every launch reports its real numbers back into the same model. What follows is what sits underneath it.
The studio seen from above — a store being read, a forecast being drawn, three categories still waiting on a verdict. Measurement, made into a picture.
Ria KimChief Design Officer
Platform
The platform our team works on is built in-house. It is the reason a small studio can evaluate a market properly.
A daily batch pulls store charts, keyword suggestions, competitor install brackets, ratings and review histograms. Every record is tagged with a reliability grade, and low-grade data is never allowed to calibrate a forecast.
Candidates are ranked on demand, supply weakness, entry difficulty and expected revenue. The model explains its reasoning per candidate, so a low score can be argued with rather than obeyed.
Before we build, a cohort model projects installs, retention and unit economics, then runs a Monte Carlo across the uncertain inputs. We look at the pessimistic case first, and it is the one that has to clear.
Live apps report retention, stability and revenue back into the same model. Every launch makes the next forecast less of a guess — which is the part a spreadsheet cannot do.
Company
Contact
Support, business enquiries and policy questions all go through the same form. We answer within two business days.