SCAPTION launches real-time speech captioning and translation in 58 languages for live events, delivering sub-two-second latency directly to venue displays and attendee smartphones.
SCAPTION is an AI-powered live captioning and simultaneous translation platform built for conferences, public ceremonies, and corporate events. The software converts live spoken audio into captions and translations across 58 languages with under two seconds of latency. Event organizers can route captions onto venue screens using transparent NDI sources or chroma-key HDMI video feeds, while attendees can access live text or audio streams on their own smartphones via a QR code without downloading an app or creating an account. In addition to multilingual accessibility, SCAPTION integrates audience engagement tools such as moderated Q&A, live polling, and automated post-session AI summaries.
SCAPTION takes direct aim at expensive simultaneous interpretation setups and enterprise-gated competitors like Wordly and Interprefy by turning live multilingual accessibility into a transparent, self-serve AV utility.
- –Frictionless audience onboarding: QR-code browser access removes app installations and login friction, significantly increasing in-room adoption.
- –Broadcast-ready AV integration: Native support for transparent NDI feeds and chroma-key HDMI fits directly into professional event production setups.
- –Cost and accessibility disruption: Eliminating per-attendee surcharges and human interpreter overhead makes multilingual events viable for smaller organizers and universities.
- –Comprehensive session tooling: Bundling live translation with moderated Q&A, audience polls, and automated session summaries provides an all-in-one event engagement stack.
- –Real-world audio challenges: Maintaining high translation fidelity and contextual accuracy in noisy event halls across technical domain jargon will be the key test against human interpreters.
DISCOVERED
2h ago
2026-09-13
PUBLISHED
8h ago
2026-09-13
RELEVANCE
AUTHOR
Luis Miguel Burgaz Olmeda