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Meet the T Challenge 2026 Finalists

The future of telecommunications is no longer just a vision—it is becoming AI-native. Today, we are thrilled to announce the top 12 teams selected for the T Challenge 2026. These innovators are at the forefront of a global movement to build autonomous, customer-focused, and intent-based network ecosystems.

This year’s competition drew revolutionary ideas from startups and research pioneers worldwide, all focused on leveraging AI to reshape connectivity. From a massive pool of talent, 12 standout teams have been chosen to advance, representing the pinnacle of innovation in three strategic pillars:

  • Autonomous Networks: Systems that think, adapt, and heal themselves.
  • Energy Efficiency & Zero-bit Zero-watt: Groundbreaking solutions to minimize energy consumption across the network.
  • Security: Advanced threat detection and the protection of AI models themselves.

What’s Next?

The journey is just beginning. Starting February 2, 2026, these finalists enter the Development Phase. Over the next three months, they will collaborate directly with experts from Deutsche Telekom and T-Mobile US to refine their prototypes and prepare for the global stage.

The competition will culminate in a live pitch and award ceremony at the Telekom Headquarters in Bonn, Germany, on April 28 and 29, 2026. Here, teams will compete for a slice of the €300,000 (or U.S. equivalent) prize pool and the chance to transform their visions into real-world game-changers for millions of customers across Europe and the U.S.

Join Us in Shaping the Future

T Challenge 2026 is more than a competition—it is a transatlantically fueled engine for innovation. Stay tuned as we follow these 12 teams on their road to the finals in Bonn!

T Challenge Nominees 2026

AnyOPS

Italy

FiberBot – Autonomous Robotic Platform for Intelligent Network Maintenance

FiberBot is an autonomous robotic platform that brings execution to the physical layer of telecom networks, performing optical diagnostics and transceiver replacement in live data centers. Enhanced with AI-based anomaly detection, it transforms physical maintenance into a closed-loop element of the Autonomous Network architecture. This increases infrastructure availability and significantly optimizes operational efficiency.

zTouch Networks

United States

zTouch.OS: Intent-Driven Autonomous Network Management for Sustainable and Monetizable AI-RAN

zTouch.OS provides intent-driven autonomous management for sustainable AI-RAN. It streamlines 5G operations through AI-native orchestration, reducing technical complexity and operational costs. The platform enables dynamic resource allocation and service-oriented slicing, transforming the network into a flexible infrastructure capable of supporting monetizable location-based AI services.

Telorics

United States

Telorics Agentic AI: Enabling Autonomous, Predictive, and Scalable Network Deployments

Telorics delivers an Agentic AI system that fully automates RAN infrastructure deployments. By streamlining structural analysis, material procurement, and crew selection, it ensures optimal network upgrades with significant CAPEX/OPEX savings. This solution maximizes asset lifetime value and enables MNOs to achieve autonomous, predictive, and scalable infrastructure management.

ValueGrid

United Arab Emirates

Blacklight Network - Revealing hidden risks in autonomous networks

Blacklight Network is an AI-native discovery engine that stress-tests digital twins to uncover hidden failure modes. By simulating complex traffic shocks, it identifies risks before they impact customers. This proactive approach ensures SLA compliance and enhances the resilience of intent-based orchestration in autonomous architectures.

CUBIG

Republic of Korea

LLM Capsule: Real-time PII Guardrail & Audit Trail for Accelerated, Auditable AI Operations

LLM Capsule provides a real-time security layer for AI operations, ensuring PII protection and a comprehensive audit trail. By automating data masking and compliance monitoring, it allows telcos to bypass regulatory bottlenecks and accelerate AI deployment. It creates a secure environment for cross-border data collaboration and auditable autonomous processes.

Vigilent

United States

AI-Driven Cooling Optimization

Vigilent is an AI-driven optimization solution that uses machine learning and sensors to dynamically control data center cooling. By matching environmental controls to the IT load in real-time, it ensures a perfect thermal environment while maximizing energy efficiency. This reduces operational risk and lowers carbon emissions by up to 50%.

Companion.energy

Belgium

Transforming Telekom’s Network into an AI-Driven Virtual Power Plant

Companion.energy transforms distributed telecom infrastructure into a coordinated AI-enabled Virtual Power Plant (VPP). By unifying operational and market data, it identifies demand-shifting opportunities. This reduces energy costs and CO2 emissions, turning passive network assets into active, monetizable participants in the green energy grid.

Daisytuner

Germany

Turbocharging AI Efficiency: Every Watt Counts

Daisytuner is an AI-driven compiler that optimizes AI workloads for heterogeneous hardware, eliminating vendor lockin. By maximizing throughput and minimizing energy-per-inference, it enables telcos to deploy models across energyefficient accelerators seamlessly. This provides a pathway to sustainable, cost-effective, and scalable AI operations at scale.

Stanford University

United States

Knowledge-Driven Edge-Cloud Link for AI-Native Telecommunication

This framework transforms AI into a core element of the communication layer via semantic compression. By utilizing sharedmemory, devices transmit only contextually relevant information, delivering double-digit energy savings. This vendor-agnostic software optimizes bandwidth, providing a scalable path toward the Zero-Bit Zero-Watt network vision.

Excalibur

Slovakia

AI-Native Telco-Scale Secure Access: Inverting the Economics of Cyber Warfare

Authentic8 is an isolation-first Secure Access fabric that eliminates the network-layer attack surface by terminating sessions within operator infrastructure. Delivering only a visual stream to endpoints, it renders vulnerabilities irrelevant. This transforms cybersecurity into a high-margin managed service, reducing TCO while ensuring zero-day  resistance at telco scale.

Spotlight

United States

Agentic Network Security: AI That Fixes, Not Just Finds

Spotlight Security leverages agentic AI to automate the complete vulnerability remediation loop. Unlike traditional tools, it analyzes risks and executes specific fixes with human-in-the-loop oversight. This shrinks remediation time from days to minutes, reducing SOC workloads while ensuring consistent policy enforcement across distributed network environments.

SelfHack AI

Finland

AI Agentic Penetration Testing Platform

SelfHack AI is an autonomous system providing continuous agentic penetration testing to discover and verify vulnerabilities at scale. By automating threat reproduction and compliance reporting, it accelerates detection by 90%. It transforms security into a measurable, real-time business control, reducing remediation effort across complex, AI-native telco infrastructures.

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