Frogy LIVE Powers Premium Video Through dTelecom's Decentralized Infrastructure

**dTelecom introduces decentralized infrastructure layer for real-time AI applications** dTelecom has launched a DePIN (Decentralized Physical Infrastructure Network) layer on Solana designed to support real-time AI operations. The platform addresses a critical gap in current AI infrastructure by providing the real-time coordination needed for AI agents and applications. **Key features include:** - Live coordination loop connecting AI agents, data, and users - Sub-second latency across 4 continents - APIs and SDKs for voice, video, and screen-share integration - AI-native architecture for translation and moderation **The infrastructure challenge** While AI applications are moving to decentralized networks, most still rely on centralized communication infrastructure. dTelecom's solution provides verifiable, open-source real-time communication that can scale without vendor lock-in. The platform offers developers transparent pricing and composable tools for building applications that require live interaction and coordination. **Available now** Developers can access dTelecom's API and SDK to integrate real-time capabilities into their applications. The infrastructure supports the growing demand for AI applications that need to coordinate and communicate in real-time across decentralized networks.

**83% of enterprise communications** pass through undisclosed intermediaries, violating regional data laws according to NYT's April report. The EU's DSA and UK's Online Safety Act now make companies **liable for unknown routing paths** - if your call crosses undisclosed routes, you're responsible. **dTel's solution:** - Every node staked & registered on-chain - Cryptographic proofs for each relay - Real-time auditable routes from user to ledger This shifts from *privacy by policy* to **transparency by design**. For enterprises: compliance you can prove For builders: trust you can verify Audit trails become protocols, not PDFs.

**Speed meets trust** in edge computing infrastructure development. A new approach to data pipeline architecture emphasizes that while **speed acts as the engine**, **verifiability serves as the steering wheel** for reliable data delivery. Key developments: - Verifiable pipelines built at the edge - Focus on delivering both fast and trustable data paths - Integration of speed with verification mechanisms This infrastructure approach addresses the critical need for **high-performance data delivery** while maintaining **trust and transparency** in the process. The concept builds on previous work connecting Ethereum (ETH) as the foundational engine, EigenLayer (EIGEN) as an accelerator, and verifiable cloud infrastructure as the highway for **top-speed verifiability**. This development represents progress toward more reliable decentralized infrastructure that doesn't sacrifice trust for performance.

**AI infrastructure is fundamentally shifting** from centralized data centers to distributed edge computing networks. - Cisco and other $50B+ infrastructure companies are moving compute closer to users - The next decade will focus on **millions of micro-AI nodes** rather than larger cloud systems - Each node must prove its integrity in real-time through verifiable processes **dTel_org has built a solution** - a verifiable mesh network where: - Every interaction (frame, packet, inference) is cryptographically signed - All processes are timestamped and trustless by design - Real-time AI operations can maintain data integrity This shift addresses critical issues with centralized systems: - **Unacceptable latency** for real-time applications - Data sovereignty concerns - Need for local processing of sensitive information The infrastructure enables secure, decentralized computation on locally-generated data while maintaining privacy and performance standards required for physical AI applications like robots, drones, and wearables.