Search Hook: CogniPath IoA Gateway integrates with Cisco Outshift’s AGNTCY Internet of Agents, enabling ACP-over-CogniPath routing, OASF directory registration, and LM-driven path selection for IoA-compatible multi-agent workflows.

CogniPath™

Intent-Driven Networking Powered by Distributed Language Model Agents

Overview

CogniPath™ is a next-generation intent-driven packet networking system that leverages distributed language model (LM) agents to dynamically determine packet routing paths in real time. Instead of static configuration or legacy routing convergence delays, CogniPath™ embeds intent directly in packet metadata, enabling an intelligent, adaptive network that reacts instantly to topology changes, failures, and evolving policy requirements.

Unlike traditional routing protocols (BGP, OSPF, EIGRP), CogniPath™ dynamically adapts to the actual intent of the packet using on-demand inference, enabling:

• Adaptive routing based on live topology and telemetry.
• Real-time rerouting around failures or degraded links.
• Compatibility with legacy protocols via a protocol-agnostic interface.

Release Information

Version: v0.1.0 Initial Public Pre-release (Public Architecture Preview)

See the Release Notes for details.

Key Innovations

1️⃣ Decentralization + Packet-Level LM Intent

• Each packet carries embedded intent in its header/payload.
• Nodes act as autonomous LM agents interpreting this intent.
• Eliminates reliance on a single centralized controller.

2️⃣ Agentic Consensus + Determinism via LM

• Distributed LMs act as decision agents to agree on optimal paths.
• Security hardened by token-hashing, UUID replay prevention, and consensus thresholds.
• Ensures deterministic decision outcomes in distributed settings.

3️⃣ Control-Plane Intelligence Shift

• Moves decision-making to the edge control plane.
• Routing decisions are triggered dynamically by packets rather than static policies.
• Enables continuous optimization as topology evolves.

4️⃣ Adaptive Switching (Phase 4 Feature)

• Next‑generation replacement for spanning tree.
• Keeps all links active while preventing loops in real time.
• Dynamically adapts switching paths based on LM-driven network intent and live health telemetry.

5️⃣ Wireless-Ready Adaptive Framework

• CogniPath’s architecture is designed for wireline and wireless environments, including LoRaMesh, Wi‑Fi 6, and 5G.
• Intent‑driven routing seamlessly adapts to variable wireless link quality and mobility conditions.
• Wireless capability is enabled through the same LM‑driven control plane, ensuring link resilience and real‑time rerouting without protocol‑specific dependencies.

Suggested Augmentations (Included in Roadmap)

• LM Prompt Adaptation: Mutates LM inputs dynamically (e.g., excludes failed nodes) based on telemetry.
• LM Response Auditability: Logs LM decisions in signed, traceable formats (logs/lm_decisions.log).
• Protocol-Agnostic Compatibility Layer: Translates LM-generated paths to legacy protocol equivalents (e.g., OSPF/BGP route injection).
• Adaptive Switching: Introduces LM-driven loop prevention and multi-path utilization for switching fabrics.
• Enterprise-Grade Switch Integration Demo
  • Deployment of CogniPath-core in containerized environments (e.g., Arista EOS container-manager, Cisco IOx, Junos OS Evolved, etc.) on high-performance enterprise switches.
  • Showcases LM-driven routing operating in parallel with traditional control planes.
  • Illustrates intent-aware routing capabilities on enterprise hardware without exposing proprietary mechanisms.

Repository Structure (Public-Safe Layout)

CogniPath/
│
├── config/                # Configuration files
│   └── lm_roles.yaml      # Defines LM roles: CogniCore™, CogniEdge™, CogniLite™
│
├── core/                  # Public-safe core architecture
│   ├── README.md          # Core overview (public-safe)
│   ├── __init__.py        # Package initialization
│   ├── agent.py           # LM orchestration layer (sanitized)
│   ├── node.py            # Node logic abstraction (sanitized)
│   ├── packet.py          # Packet structure & public-safe processing
│   ├── tokenlib.py        # Public-safe token validation
│   └── utils.py           # Utility functions
│
├── docs/                  # Documentation
│   └── README.md          # High-level technical overview
│
├── legacy_compat/         # Legacy routing protocol stubs (no LM logic)
│   ├── bgp/
│   │   └── parser.py      # BGP compatibility stub
│   ├── eigrp/
│   │   └── parser.py      # EIGRP compatibility stub
│   ├── ospf/
│   │   └── parser.py      # OSPF compatibility stub
│   └── README.md          # Legacy compatibility overview
│
├── logs/                  # Logs & auditing (public-safe)
│   ├── README.md          # Logging overview
│   ├── agent_audit.log    # LM agent audit trail (public scrubbed)
│   └── lm_decisions.log   # LM decision logs (public scrubbed)
│
├── tests/                 # Public-safe test suite
│   ├── README.md          # Overview of testing framework
│   ├── __init__.py        # Package init for test discovery
│   ├── test_agent.py      # Tests for agent abstraction layer
│   └── test_packet.py     # Tests for packet structure
│
├── .gitattributes         # Public repo IP boundaries & file handling
├── .gitignore             # Ignored files for public repo safety
├── LICENSE.md             # Proprietary license for CogniPath
├── NOTICE.md              # IP protection notice & patent language
├── README.md              # This file (overview & documentation)
├── main.py                # Demo entry point for public build
└── requirements.txt       # Public-safe dependencies

Intellectual Property & Licensing

This public repository contains a limited, public-safe subset of CogniPath’s architecture.
Core intellectual property (LM internals, consensus algorithms, advanced prompt structures, and production routing logic) is maintained in the private CogniPath-core repository.

Patent protection is in process via USPTO Provisional Patent Application (PPA) covering:

• LM intent-embedded packet networking.
• Distributed LM consensus routing.
• Edge-triggered control plane inference.
• Adaptive Switching (loop-free multipath switching).

Installation & Quickstart

Clone the repository:

git clone https://github.com/<your-org>/CogniPath.git
cd CogniPath

Create a virtual environment & install dependencies:

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run the demo:

python3 main.py

Legacy Protocol Compatibility

CogniPath™ supports interoperation with existing networks by translating LM-decided paths to formats understood by:

• OSPF
• BGP
• EIGRP

Note:
Legacy protocol translators in legacy_compat/ are public stubs. Full compatibility modules are maintained in private protected code.

License & Notice

This public repository is released under a restricted license.
Use is allowed for educational/research purposes.
Production/commercial usage without explicit permission is prohibited.

See NOTICE.md for detailed IP and licensing terms.

Learn More

• Patent Status: PPA filed (USPTO)
• Private Repo: CogniPath-core (invite only)
• Public Roadmap:

Current Phase Status

• Phase 2 (Stable) – Core LM intent routing complete
• Phase 3 (In Development) – Expanded interoperability, observability, and edge readiness
• Phase 4 (Planned) – Advanced wireless adaptation, security, and enterprise integration

Phase 3: Interoperability, Compliance, and Edge Readiness

• Protocol Interoperability – Ensure compatibility with major routing protocols.
• Resilience Enhancements – Adaptive LM-driven routing that dynamically adjusts to real-time conditions.
• Performance Optimizations – Efficient packet management with enhanced telemetry and dynamic reroute.
• Scalable Management – Configurable policy modules and topology loaders for flexible deployments.
• Observability – Expanded logging, audit trails, and dashboard integration for operational insight.

Phase 4: Advanced Wireless, Security, and Enterprise Integration

• Wireless Network Adaptation – Mobility support across multiple wireless mesh technologies.
• Security & Trust – Strengthened replay protection, multi-agent consensus, and trust-weighted decision layers.
• LM Orchestration – Cooperative operation of different LM sizes for optimal performance.
• Enterprise Integration – Deployment in containerized environments on enterprise-class network hardware.

Community & Contact

We welcome constructive collaboration, issue reports, and discussions.

Contact: Keenan Williams at telesis001@icloud.com