About Trusted Collaboration Tunnel

Mission

The Trusted Collaboration Tunnel (TCT) protocol establishes a new standard for efficient, verifiable content delivery to AI crawlers and automated agents. Our mission is to reduce global bandwidth consumption while improving AI content quality through standardized, template-invariant fingerprinting and conditional request discipline.

The Problem

Traditional AI crawlers fetch full HTML pages repeatedly:

103 KB average per page (HTML with templates)
13,900 tokens for AI processing
90%+ redundant fetches when content unchanged
No standard for machine-readable endpoints
No verification of content authenticity

The Solution

TCT provides a 4-part protocol:

Bidirectional Discovery – Verifiable C-URL ↔ M-URL handshake
Template-Invariant Fingerprinting – SHA-256 content hashes
Conditional Request Discipline – 304 Not Modified responses
Sitemap-First Verification – Zero-fetch optimization

Measured Results

Based on 970+ URLs across 3 production websites:

83% bandwidth savings (103 KB → 17.7 KB)
86% token reduction (13,900 → 1,960 tokens)
90%+ skip rate for unchanged content
100% protocol compliance achievable
8,158 GWh/year potential energy savings

Patent-Pending Technology

US Patent Application 63/895,763
Filed: October 8, 2025
Status: Patent Pending

Key innovations:

Template-invariant content fingerprinting
Bidirectional URL handshake verification
Sitemap-first zero-fetch optimization
Optional trust extensions (auth, receipts, policy links)

Open Source Implementation

Free for Website Owners:

WordPress plugin (GPL v2+)
Cloudflare Worker (MIT)
Python client library (MIT)
Complete documentation

Commercial Licensing:
Large-scale operators (AI companies, CDNs, crawler services) processing >10K URLs/month should contact us for licensing terms.

IETF Standards Process

We’re pursuing standardization through the Internet Engineering Task Force (IETF):

Specification: draft-jurkovikj-collab-tunnel-00
Target: IETF 125 (March 2026)
Working Group: GREEN (energy efficiency)
Status: Under development

The energy efficiency section demonstrates:

0.06 kWh/GB network transmission savings
0.000187 kWh/token AI inference savings
Scaled to 8,158 GWh/year at 10% adoption

Production Deployment

Live Sites (100% Compliant):

wellbeing-support.com – 400 URLs, 10/10 score
galaxybilliard.club – 500 URLs, 10/10 score
bestdemotivationalposters.com – 500 URLs, 9/10 score

Total: 970+ URLs with full protocol compliance

Validation: llmpages.org/validator

Team

Antun Jurkovikj – Creator & Lead Developer

Background in web optimization, AI integration, and energy-efficient protocols. Committed to reducing global bandwidth consumption while improving AI content quality.

Contact: [email protected]
GitHub: github.com/antunjurkovic-collab

Timeline

October 8, 2025: Provisional patent filed (US 63/895,763)
October 17, 2025: Python library published to PyPI
October 18, 2025: Cloudflare Worker published to GitHub
October 18, 2025: Energy efficiency section added to IETF spec
November 2025: WordPress plugin submission (pending)
March 2026: Target IETF 125 presentation