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Stop guessing what to fix next
Turn player feedback and
gameplay signal into
clear next steps
Collect player feedback across channels, link it to real gameplay sessions and locations, and produce an investigation plan, reproducible examples, and fix recommendations (UE5).
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How it works
Gameplay Diagnosis
Copilot
An expert-grade copilot that learns your game’s systems and design intent over time. It understands your vocabulary, mechanics, and player context, and helps the team align faster.
Player Feedback
Dashboard
Stop chasing voice across tools. SimMind pulls player feedback into one place, groups it into clear themes, and helps you decide what to fix first.
More channels coming: Discord, Steam reviews, surveys, support tickets.
AI-Powered Investigations
Games are dynamic: difficulty, pacing, level layout, and player skill all interact, so the “real cause” is often hidden.
SimMind Investigations help team measure what’s actually happening inside the game.
You instrument a small set of events in UE5, capture player behavior during playtests, and understand what’s really broken in gameplay.
UE5 Plugin
(In-Engine Debugging)
Taking every finding from the console and letting you jump back to the exact in-game location with full context.
- Heatmaps & Movement Paths: instantly see hotspots, dead zones, and the routes players actually take.
- Player Playback: replay real sessions as a “pre-issue window”, with event markers and timestamps.
- Analyze: bring web insights into UE5 , query a finding and see it directly in the level.
Where this fits in the Game Dev Cycle
- Every game hits the same wall mid-cycle: you get a lot of playtest feedback, but it’s hard to tell what’s real and what to fix next.
- The real gap is visibility—teams can’t see how players actually move, struggle, or make decisions in the game.
SimMind brings player voice and player behavior together, then carries it through the rest of the loop. Ask questions in the chatbot with full in-game context, start an investigation, and jump into UE5 to debug and verify. So playtest feedback turns into real fixes, faster.
How we understand your game？
Context-aware
Understands what happened around an issue—session, checkpoint, encounter, and timing.
Spatial-aware
Sees where it happens—hotspots, paths, zones, and level segments (from UE5 spatial scans).
Intent-aware
Keeps your design goal in the loop—what the experience should feel like, and where reality diverges.
How we turn signals into decisions
Evidence-first
Connects every claim to supporting sessions and signals—so teams don’t debate in circles.
Gets sharper over time
Improves as you confirm what’s true in your game and add the instrumentation you actually need.
Game-specific
Built around gameplay primitives (checkpoints, deaths, encounters, progression)—not generic text summaries.
By capturing data at this deeper cognitive level, SimMind enables developers to build games that truly understand and adapt to players in meaningful ways.
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