altered brilliance
B2C
Player-facing product experience
ALTERED BRILLIANCE IS LIVE ON GOOGLE PLAY. Read the product story →
Codename-TGX1 interprets the structured cognitive context created by tGiX, using a specialised gaming SLM rather than asking a general-purpose model to decode raw telemetry.
Every TGX1 variant interprets structured context from tGiX. The model code signals the product environment and the people it is built to serve.
The player-facing TGX1 variant for Altered Brilliance, bringing tGiX-produced context into the product experience.
The development variant for studio workflows and the tGiX marketplace, bridging player-facing and game-development-facing data.
The enterprise variant of the TGX1 model family, scoped for organisations building on the structured context layer.
The education variant of the TGX1 model family, designed for learning-focused programmes and partner environments.
The competitive-performance variant of the TGX1 model family for eSports organisations and their workflows.
TGX1 is a unified SLM family, with model variants assigned to the commercial and product contexts where they create the most value.
altered brilliance
B2C
Player-facing product experience
tGiX marketplace
B2B2C
Player product and marketplace development for studios
Game Studios
B2B
Player-facing data and game-development-facing data
Enterprise
B2B
Enterprise product and platform environments
Education
B2B
Education programmes and partner environments
eSports
B2B
Competitive-performance environments
altered originals
B2C
Original player experiences and development workflows
TGX1 operates as localized edge intelligence, turning tGiX-produced behavioural context into predictive career translations and cognitive tilt alerts.
Designed to run locally on client devices or low-cost B2B edge nodes, delivering inference response times under 15ms without cloud dependencies.
Trained on verified, tGiX-structured gaming context rather than open-web text, allowing the SLM to stay specialised in its interpretation task.
Generates real-time predictions of player fatigue, tilt escalation, and cognitive saturation before performance collapse occurs.
| Specification Parameter | Value / Standard | Technical Details |
|---|---|---|
| Parameter Size | 3.8B Quantized (4-bit) | Optimized for edge execution |
| Inference Latency | < 15ms TTFT | Real-time structured-context interpretation |
| Training Set | 18,000+ Verified Hours | Closed-loop tGiX-derived context |
| Hardware Support | NVIDIA TensorRT, Apple Neural Engine, ONNX | Cross-platform acceleration |
| Deployment Mode | On-Device SDK or B2B Cloud API | Zero data leakage |
| Model Family | PRO · DEV · CORP · EDU · ESP | Variants aligned to player, studio, enterprise, education, and eSports environments |
Scope a model-family conversation around your product, studio, enterprise, education, or eSports environment.