MeetEase: AI-Native Video ConferencingMeetEase

Most video apps add AI afterwards, as a summary email that arrives an hour later. In MeetEase, transcription and the copilot are two ends of one pipeline. Most of the work went into making that pipeline feel instant and into keeping the app up when its external services aren't configured.

Every external dependency fails soft and independently. The Clerk handler is built only when a key exists and is wrapped in a try/catch that falls back to NextResponse.next(), so an auth misconfiguration cannot take the site down. The /api/ai route pipes Anthropic's SSE stream through a ReadableStream transformer that parses each event and re-emits only the text deltas, so tokens render as they arrive, with a clearly labelled offline fallback when there is no key. The key change was putting transcription and the copilot behind one MeetingIntelligence context: the microphone writes to the same state the copilot reads, which turned two demos into one pipeline.

Ask the copilot to summarize or pull action items mid-call and it answers from the words spoken, streamed token by token. Guest "explore mode" means no login wall. Missing configuration cannot crash the app, so it deploys and loads on Vercel with no environment variables set, and adding keys turns features on one at a time.

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The /api/ai route has no rate limiting yet, and I would add it before the app sees real traffic. Transcripts aren't persisted and speaker diarization is client-side only. Server-side diarization and a stored transcript history are the next steps.