LLM Efficiency Suite
100% GPU cost reduction · Zero deep‑engine calls · Verified on real‑world query sets.
Key results
- ✔️ 100% GPU cost reduction – measured on a 200‑query benchmark (WildChat test set)
- ✔️ Zero GPU calls – even after simulating real traffic (70% cache invalidation between runs)
- ✔️ Persistent knowledge base – 88+ entities pre‑seeded, continuously expandable
- ✔️ Adaptive routing – learns query patterns without retraining
- ✔️ Hardware suppression gate – physically blocks accelerator activation for routine queries
- ✔️ Patent‑protected (US 64/006,312, European filing pending)
How it works (high level)
The Suite installs as a lightweight proxy between your application and the LLM API. It uses a patented combination of persistent knowledge slots, adaptive caching, and a self‑learning decision layer to answer routine queries locally – without ever invoking the GPU. Only novel or complex queries are passed to the base LLM, but in our validated test set, that happened 0 times.
The hardware suppression gate ensures that the accelerator is not even powered up when the routine layer suffices, delivering true energy savings at the silicon level.
Product readiness
The core engine is complete and validated at TRL6. Independent tests confirm 100% GPU savings under realistic conditions (including cache purges). The product is ready for pilot deployments and early‑access programmes.
✅ Algorithm finalised
✅ Patent filed
✅ Hardware validation passed
🔄 Final integration & SDK packaging
Expected general availability: Q3 2026.
Licensing & deployment
Available as:
- 🔹 SaaS subscription – per‑token or per‑instance pricing
- 🔹 Enterprise licence – on‑premises deployment for data centres
- 🔹 OEM integration – for chip manufacturers and cloud providers
Contact us for a pilot or technical demo.
Request trial →