ENGINEERING DATA FOR
SMALL FORM FACTOR BUILDS
SFFLABS (sff.gg) bridges the gap between published hardware specifications and real-world fitment through deterministic geometry, spatial and relational logic, machine learning and verified build data.
Deterministic Logic
Evaluates case layouts, component dimensions and hardware specifications in real time using deterministic clearance rules, bounding-box geometry and relational compatibility logic. Known measurements and case-specific constraints remain authoritative for physical fitment.
EDGE AI
Lightweight 35–60 MB ONNX neural models run locally in the browser using hardware-accelerated WebGPU/WASM inference. The Edge-AI layer learns relational component interactions and build patterns that extend beyond deterministic dimensional checks.
BACKEND LLM (OPTIONAL)
Optional Large Language Models transform structured compatibility results into detailed, case-specific technical reports. The LLM interprets and explains the platform's evidence; deterministic measurements and compatibility logic remain authoritative for physical fitment.
3D Workbench
Interactive browser-based 3D visualisation web tool for SFF hardware and enclosures. Compare mITX and mATX case dimensions, explore hardware placement, simulate custom enclosures and test build configurations using components from the SFFLABS hardware library.
REVIEWS & COLLABORATION
We work with hardware and case manufacturers on technical reviews, hands-on fitment validation, clearance testing and thermal analysis.