Drop in a pitch and reference games. Get a full breakdown of whether it's worth it, how to position it, and what the pitfalls are.
Learn about the pitfalls and sharpen the pitch before mistakes get expensive.
Blitz doesn't guess. Every verdict traces back to real player reviews — processed, classified, and counted by Mappex infrastructure before the model writes a single sentence.
We're processing new games 24/7. If your reference games aren't in our database yet — no worries, Blitz will run the analysis on demand.
Each reference game gets a full breakdown — strengths, weaknesses, what to borrow, and what to avoid. Backed by real player feedback, not opinions.
Pitchability, scale potential, and execution difficulty scored on a 3-point scale. Know if the concept is worth pursuing before committing.
Suggested price range, audience size, and market positioning — so you pitch the right game to the right players.
The three failure modes most likely to sink the concept, plus hard kill criteria that tell you when to stop.
The strongest lanes to build toward — what to prototype first, what to playtest, and what to expand later.
A phased roadmap with team size, priority, and expertise tags for every step from prototype to production.
Blitz helps you understand what your reference games imply for your own project before those decisions become production debt.
Because a general-purpose chat model can make this kind of research sound convincing without grounding it in enough evidence.
A single prompt usually reads only a thin slice of store pages, articles, or reviews and then extrapolates from that sample. Models are also unreliable at counting disputed signals, and their context windows are too small to ingest a statistically meaningful amount of player feedback for each reference game.
Blitz runs on Mappex pipelines instead. For each reference game, it processes large volumes of player feedback, extracts and counts signals outside the model, and only then uses AI to synthesize the report.
ChatGPT answers can look similar and convincing, but without real counting they are still guesses, and any mistake at that level pushes the final conclusions off course. Mappex does not have that problem.
Because it shows the hidden baggage that comes with your references, so you can catch fake depth, readability debt, and progression traps early.
No. But you can check demo report to see what the result looks like and assess the quality.
There are no refunds. However, if there is any bug or other issue with the report, contact mappex.ai@gmail.com with the report link and we will fix it for free.