Powering network delivery for the AI-native era

Distributed MCP is in build. See how legacy delivery collapses before we rewire it for intelligent workloads.

Understand the Gap Preview the Vision
Why This Work Exists

AI-native experiences ask networks to read context, not freeze bytes. This map captures the gaps guiding our build.

Legacy CDNs stall for AI-native delivery

Traditional CDNs sprint on cached HTML, media, and API calls. They win when content ships once, gets cloned everywhere, and stays static. AI-native delivery flips that script: every prompt spins something new, context mutates mid-session, and responses stay personal.

Today’s CDNs still forward blindly. On-demand output forces latency, drops session memory, and starves accelerators—the experience collapses right there.

AI-Generated Content Per-request output; caches never catch it
Edge GPU Delivery GPU-ready edges; CPU+GPU inference lands next
Context in Motion Context-aware models now run distributed by default

Where this heads

We are shaping a delivery fabric that thinks alongside its traffic. Operators will enroll idle accelerators, stitch in memory segments, and launch inference policies with the ease of pushing cache rules.

Adaptive Cognition Intent-aware routing, live observability, and shared context layers keep every response situationally smart.
Accelerator Harmony GPU-first orchestration pairs with CPU assists so inference flows across refreshed edges and reclaimed gear.
Agent Ops Ready Agents and tools plug into unified APIs so autonomous workflows feel instant, reliable, and grounded.

The destination is an AI-native internet that learns with every interaction and can deploy new intelligence the moment it is minted. Distributed MCP rewires how software, agents, and whatever comes next connect with the internet.