Introduction

The Need for Verifiable Network Intelligence

Modern economies run on network connectivity, yet reliable data about network performance and device presence remains surprisingly hard to obtain. Telecom operators publish coverage maps and uptime statistics, but these are often taken on faith and can be inaccurate or overstated. Regulators and governments subsidize broadband rollouts and enforce service obligations but lack independent tools to verify that citizens truly receive the promised quality of service. Enterprises that rely on connectivity – from cloud service providers to logistics firms – often must trust carrier reports or deploy expensive monitoring hardware, and they remain vulnerable to location-based fraud (e.g. a driver claiming to be at a delivery point when they are not, or a user spoofing location to gain access to region-locked services). The advent of autonomous vehicles, IoT sensors, and remote work means trustworthy real-world data (like “Is this device really where it claims?” or “Is the network actually performing as expected for users on the ground?”) is more critical than ever .

However, existing solutions have limitations. Traditional network monitoring platforms (e.g. Cisco ThousandEyes, Catchpoint) deploy probes in data centers or enterprise sites, capturing core network metrics but often missing the last-mile perspective of actual end users on mobile and residential networks. Crowdsourced apps like Ookla Speedtest or Opensignal gather user-generated data, but they typically rely on user altruism or curiosity, without strong incentives, and they lack verifiability – data can potentially be spoofed or may not meet rigorous evidence standards. Decentralized projects have tried to tackle pieces of this puzzle (Helium for crowdsourced wireless coverage, FOAM and XYO for location proofs, etc.), but none combine user-level network performance data with robust presence verification in one platform. Moreover, many such projects required dedicated hardware or did not gain enterprise adoption, limiting their impact.

Authra was conceived to address these gaps by creating a global, decentralized network of smartphone-based sensors that feed into a tamper-proof public ledger, making the data self-verifying. The goal is to provide a source of truth for network performance and presence that is as trusted and neutral as a financial blockchain ledger yet focused on real-world infrastructure metrics. By doing so, Authra unlocks numerous opportunities: regulators can objectively audit telecom SLAs, enterprises can get real-time performance intelligence without deploying new hardware, and new applications (like smart contracts that react to physical-world events) become possible with high assurance.

The following sections describe Authra’s architecture and approach in detail – from the blockchain layer and token economics that incentivize participation, to the AI systems that enhance data quality, to the user and enterprise interfaces that ensure wide adoption – all engineered to deliver a secure, scalable, and compliant network intelligence platform.