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

We start with a money-saving, privacy-centric B2B stack: Membria Enterprise Edition. Once it’s battle-tested inside enterprises, the same two-tier brain populates consumer devices: PC’s, Laptops, Flagship Phones and, finally AI Live Pod, Embodied AI device

And How We’ll Get There

1 · The Enterprise Beach-head — Membria EE

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

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

How it works

2 · 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.

3 · Why an “Embodied AI Device” Actually Rocks

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

4 · Roadmap Snapshot

5 · 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 🐾 ♻️.