Welcome to Membria 💭: Sustainable Hybrid AI Platform Coming First to Enterprises

And How We’ll Get There

• Skill Forge loop distills each cloud answer into a tiny LoRA patch on the laptop—personalising the model in seconds, not hours.
• ‍Gateway (LLM-router) decides in < 5 ms where each prompt should run and which knowledge chunks to fetch.

Result: up to –75% inference spend (~90% of any Gen-AI budget) with 100% data sovereignty.

How it works

From Board-room to Bed-room

Once Membria EE proves itself (predicted year-one target: –75 % GPU OPEX across energy & telco pilots), the very same brain architecture can shrink:

Because Edge handles  90% of traffic, the Knowledge Core scales elegantly: one node can serves ~100+ concurrent DoD (Distillation on Demand) requests, coming from Tiny LM to large model via Membria, not thousands of direct simultaneous user prompt queries.

Why an “Embodied AI Device” Actually Rocks

• Always on, always listening → perfect for context caching (when we’re stay away from work).
• Relax without keyboard and mouse → NUI (Natural UI: voice, eye tracking and gestures) beats chat windows.
• Household data stays inside four walls → our Edge-first philosophy in action

In other words, the cute bedside gadget is just a different skin on the hardened enterprise AI.

Take-aways

• Start with B2B where savings are undeniable → fund R&D.
• Two-tier design means one code-base, many devices.
• By the time competitors realize, Membria is already on the night-stand—ready to wake users with GPT-4 brains that cost almost nothing to run.

Membria: Big Brains 🤯, Small Footprint 🐾 ♻️.