Telos Alliance flexAI update adds autonomous mixing for live sports

The introduction of autonomous mixing via CastCompanion addresses the increasing complexity of managing audio across fragmented hardware and cloud workflows. By automating level adjustments and denoising while maintaining deterministic latency, Telos Alliance is positioning the flexAI platform as a bridge for broadcasters moving toward IP-based production without sacrificing real-time reliability. This shift reflects a broader industry trend where AI is applied to specific labor-intensive tasks like loudness management and upmixing rather than replacing the core processing path. Watch for the commercial rollout of the 12G-SDI interface in late 2026 to signal broader adoption in high-bandwidth UHD sports environments.

Telos Alliance's Jünger Audio division has been building toward autonomous audio processing for several years, positioning flexAI as a platform that combines AI-driven level control with traditional broadcast audio infrastructure. The company's broader strategy aligns with a growing trend among broadcast technology vendors embedding machine learning into production workflows. At IBC 2026, multiple vendors showcased AI-assisted audio and video tools targeting live production, reflecting demand from broadcasters seeking to reduce manual intervention in fast-turnaround environments. The flexAI platform's expansion into autonomous mixing via CastCompanion places Telos Alliance in direct competition with other real-time audio processing vendors that have begun integrating AI into their product lines for loudness compliance and dynamic range management. The business case for autonomous mixing tools like CastCompanion is driven by the economics of live sports production, where audio engineers face increasing channel counts and tighter turnaround windows. Telos Alliance has positioned its broader portfolio, including the Z/IP series and xNode platform, as infrastructure for IP-based broadcast facilities, and the flexAI update extends that IP-native approach into the audio processing layer itself. The integration with TVU MediaMesh is notable because TVU Networks has been expanding its cloud-based production ecosystem aggressively, and pairing autonomous audio with TVU's distributed media processing creates a path toward fully remote production workflows where no on-site audio engineer is required. This mirrors the broader shift in live sports toward remote integration production models that have accelerated since 2020. On the technical side, the addition of 12G-SDI and NDI connectivity to flexAI addresses a specific gap in the broadcast audio chain: the need to interface AI-processed audio with both legacy baseband infrastructure and modern IP-based production systems simultaneously. Nokia and other network equipment vendors have been pushing agentic AI frameworks for automated network operations in 2026, and while that work targets telecom infrastructure rather than broadcast audio, the underlying pattern of deploying autonomous agents to handle real-time decisions across distributed systems is directly analogous to what Telos Alliance is doing with CastCompanion. The AIXpressor algorithm, which handles dynamic range compression using machine learning, represents the kind of narrow AI application that broadcast engineers are more willing to trust than fully generative systems, because the output remains deterministic and measurable against broadcast loudness standards such as EBU R128 and ATSC A/85.