60% fewer bytes. Same instruction. Every hop.
At scale that's the difference between a breakthrough and a bill.
The Octid Semantic Mesh Protocol (OSMP) is an open encoding standard that compresses agentic AI instructions 60–87% and decodes by table lookup — no inference required at the receiving node. Any device. Any channel.
Every inter-agent instruction today is a verbose, cloud-dependent, inference-heavy payload. That works fine in a data center, but fails completely under edge constraints like the LoRa radio floor. Tokens get torched at scale, and natural language locks sovereign edge systems into infrastructure designed for full-scale models — not the lightweight agents that actually run there.
48-vector canonical conformance suite. All three SDKs verified independently. Wire compatible across Python, TypeScript, and Go.
Open source inventors and entrepreneurs who want efficiency to compound their growth — not their costs.
| Protocol | Transport | Offline | Compression | Inference-free decode | Layer |
|---|---|---|---|---|---|
| MCP (Anthropic) | HTTP/JSON | ✗ | ✗ | ✗ | Framework |
| A2A (Google) | HTTPS/JSON | ✗ | ✗ | ✗ | Framework |
| ACP (IBM) | REST/HTTP | ✗ | ✗ | ✗ | Framework |
| OSMP | Any channel | ✓ | 60–87% | ✓ | Encoding |
Apache 2.0. Python, TypeScript, and Go. The benchmark is in the repo.
Fails at 51-byte LoRa floor. Costs tokens at every hop.