Game Growth Recommendation
What to change in the live game.

Know what to grow. Build what comes next.
Immersely helps game studios manage the AI transition with a suite of AI tools. At its core is JUDE, the Game DNA knowledge layer: it sees, thinks, plays and feels a game like a player, so studios know what to grow and can build tools to create what comes next.
52 in-game KPIs · moment-to-moment · peak-end · See the full measure list
No SDK. No lab. Players play from home.
Share a build. Players play at home. You get what to grow, and what to create next. Nothing to integrate, nothing to change in the game.
Upload a build, or send a Steam key or store link. No SDK, no code changes, no engine plugins.
Your own community, or our panel, plays in their normal setup. Webcam on, their own smartwatch on, gameplay recorded.
Emotion, behaviour, and the frame land on one timeline. JUDE sees, thinks, plays, and feels that session the way a player did. The report comes back with the clips that decide what to grow and what to build next.
60 in-game KPIs
Legibility and efficiency. Goals, mechanics, and results are readable without searching.
14 KPIsCognitive state. Goal, control, and competence. Cognitive, not emotional.
3 KPIsHook, reward, mastery, friction, and momentum, minute by minute.
18 KPIsWebcam-inferred energy, mood, and tension. Always read with the on-screen frame, never alone.
17 KPIsA session is judged by its peak and its end, not its average.
8 KPIsA session is judged by its peak and its end, not its average. Duration barely counts.
In-session gameplay
Gameplay only. No webcam, no face, no player name.

The arena, the threat, and the next move are all on screen.
Mid-air engage. Is the fight still worth taking?
The shot is about to land. The beat the session will remember.
What lands on the desk
Two outputs from JUDE’s reading of the session — not a second how-it-works.
What to change in the live game.
The next encounter, built from the beat that landed.
Founder-led, science-backed
Building a hyper-fidelity foundation model for player emotion
Immersely began with founder Goodness Akalazu, an electrical engineer and roboticist asking how a machine can read the person in front of it, in real time. He built the team around that question, bringing in a Cambridge-trained physicist and AI entrepreneur and an award-winning data scientist. Since 2022 we have pointed all of it at one goal: helping studios understand their players.

CEO & Founder
Electrical engineer and roboticist turned AI researcher. He built Immersely around real-time emotion detection, the same skill a robot needs to work alongside people.

Chief Science Officer
Physicist and serial AI entrepreneur. He founded Hazy, winner of a $1M Microsoft AI Prize, and brings the science behind JUDE.

Lead Data Scientist
Award-winning data scientist working across materials engineering, biochemistry, healthcare and AI. He turns raw player signals into models studios can trust.
Advisors
Behavioural Research Analytics In Neurotechnological Systems