Short clips, instant output
A snippet from a meeting, a support call, a voice message. Upload and the text is there faster than opening your notes app.
Seconds to resultA few seconds of voice, a three-hour meeting, a full podcast. Hand it to Orpheus. AI does the transcription, subtitles, and clean-up for you. Nothing for you to manage.
Pick the path that matches your day. The console tunes itself once you sign in.
Podcasters, video makers, journalists. Drop in a recording, get a polished transcript and show notes.
Try the homepage toolMeeting recordings, customer calls, internal sessions. Searchable notes and action items, automatically.
See team plansOpenAI-compatible API. Swap base_url and your existing client code keeps working.
Read the API docsRegion-pinned deployments, BAA / DPA paperwork, dedicated CSM, custom SLAs.
Contact salesOpenAI, Google, Microsoft Azure, Deepgram, AssemblyAI, AWS Transcribe. Six of the world's top speech models, all wired into Orpheus. Whether it's a single transcript or AI running your whole voice pipeline, we pick the right one for the language, length, and audio quality.
Record a clip, or upload audio under 8 MB. No signup.
From a few-second clip to a multi-hour recording to a background voice agent, Orpheus picks the right pipeline automatically. No chunking, no transcoding, no model picking on your side.
A snippet from a meeting, a support call, a voice message. Upload and the text is there faster than opening your notes app.
Seconds to resultA full podcast, a three-hour meeting, a long interview. Drop the whole file in. No splitting, no timeouts.
Up to 2 GBNo picking a language, no checking if yours is supported. AI detects, segments, and handles accents, jargon, and mixed-language speech out of the box.
100+ languagesEvery sentence lined up with its spot in the audio. Video subs, meeting notes, jumping to a moment. Download and use, no re-aligning.
SRT / VTT downloadableSupport desks, appointment confirmations, lead qualification. Wire Orpheus into your background voice agent and the system routes to the right pipeline based on latency, audio quality, and length.
Auto pipeline routingGroup meetings, interviews, support calls. AI splits by speaker so you see who said each line. Copy for notes or quotes, no rewinding.
Speaker diarizationFrom the in-browser demo to production is a straight line. Try it, grab an API key, wire it up.
Drag in audio or video, or paste a link. Any length works.
From model selection to language detection, sentence-splitting, and time-stamping, Orpheus does it all automatically. You don't lift a finger.
Clean transcripts and subtitle files ready to download, or pushed straight to your app.
Keep your existing OpenAI() client. Swap the base URL and API key. Orpheus takes the same input shape, returns richer task metadata on the way out.
# curl · create async transcription job curl https://audio.niumedia-ai.com/v1/audio/jobs \ -H "Authorization: Bearer $ORPHEUS_KEY" \ -H "Content-Type: application/json" \ -d '{"upload_id":"upl_123","callback_url":"https://your-app.com/webhook"}' # Response { "id": "job_123", "status": "queued", "webhook": "configured" }
Five formats from the same recording. No mockups, no edits.
[00:00:03] Sarah Chen: Welcome everyone. Let's get started with the Q4 planning meeting. [00:00:12] Sarah Chen: Marcus, can you walk us through what we're proposing? [00:00:19] Marcus Reed: Sure. We've got three main initiatives lined up. The migration work that we've been talking about, new feature work for the platform, and some infra debt that's been piling up. [00:00:42] Priya Patel: Quick clarification. Does the migration bucket include the security audit work, or is that separate? [00:00:51] Marcus Reed: Good question. Let me come back to you on that. I think it should be separate, but let's confirm before we lock the budget. [00:01:05] Sarah Chen: Okay, so the rough split is 40-30-30 with that caveat. Marcus to confirm scope of migration. Anything else?
1 00:00:03,210 --> 00:00:11,540 Sarah Chen: Welcome everyone. Let's get started with the Q4 planning meeting. 2 00:00:12,180 --> 00:00:18,420 Sarah Chen: Marcus, can you walk us through what we're proposing? 3 00:00:19,000 --> 00:00:41,180 Marcus Reed: Sure. We've got three main initiatives. Migration work, new feature work for the platform, and some infra debt that's been piling up. 4 00:00:42,300 --> 00:00:50,890 Priya Patel: Quick clarification. Does the migration bucket include the security audit, or is that separate?
## Q4 Planning Meeting -- 2026-04-28
### TL;DR
40-30-30 split between migration, new feature work, and infra debt.
Marcus to confirm whether security audit work falls inside the 40%
migration bucket before the budget is locked.
### Decisions
- Q4 budget split: 40% migration / 30% new features / 30% infra debt
- Marcus owns scoping the migration work
- Sarah owns priority sequencing across all three buckets
### Action items
- [ ] Marcus Reed: Confirm scope of "migration" -- does it include
the security audit?
- [ ] Priya Patel: Hold the budget envelope until Marcus comes back
- [ ] Sarah Chen: Send the 40-30-30 split memo to leadership channel
### Open questions
- Does migration include the security audit, or is that separate?
- Are we hiring before or after Q4 kickoff? {
"id": "job_8a7c3f9b2e1d",
"status": "completed",
"language": "en",
"duration_seconds": 73,
"created_at": "2026-04-28T15:34:21Z",
"completed_at": "2026-04-28T15:34:54Z",
"transcript": "Sarah Chen: Welcome everyone. Let's get started...",
"segments": [
{
"id": 0,
"start": 3.21,
"end": 11.54,
"speaker": "speaker_a",
"text": "Welcome everyone. Let's get started with the Q4 planning meeting."
},
{
"id": 1,
"start": 12.18,
"end": 18.42,
"speaker": "speaker_a",
"text": "Marcus, can you walk us through what we're proposing?"
}
],
"speakers": [
{ "id": "speaker_a", "label": "Sarah Chen" },
{ "id": "speaker_b", "label": "Marcus Reed" },
{ "id": "speaker_c", "label": "Priya Patel" }
]
} POST https://your-app.example.com/webhooks/orpheus
Content-Type: application/json
X-Orpheus-Event: job.completed
X-Orpheus-Signature: t=1714368912,v1=a3b2c1d4e5f67890ab
{
"event": "job.completed",
"job_id": "job_8a7c3f9b2e1d",
"workspace_id": "ws_8f2a1b9c",
"duration_seconds": 73,
"result_url": "https://audio.niumedia-ai.com/v1/audio/jobs/job_8a7c3f9b2e1d/result",
"completed_at": "2026-04-28T15:34:54Z"
}
# Verify in your handler:
# const expected = hmac_sha256(workspace_secret, t + "." + body)
# if (received !== expected) return 401
# if (Date.now()/1000 - t > 300) return 401 # reject replays A steady wall of operator notes across creator, research, clinical, sales, engineering, and compliance workflows.
I used to dread Sunday afternoons. Cleaning up podcast transcripts by hand was the part of the job I hated most. Now I upload, walk away, come back to a polished transcript and show notes already done. I genuinely enjoy podcasting again.
Didn't think I'd find a transcription tool that handles interview recordings with the sensitivity my work needs. The accents, the overlaps, the long silences. Orpheus just does it. I don't have to fight the output. It's the first one that didn't make me cry.
Session notes used to eat my evenings. Every. Single. Day. I'd sit at the dining table writing while my family ate dinner without me. Now I record (consent first), hand it to Orpheus, and have my evenings back. My partner thanked Orpheus before I did.
Honestly tried to resist switching. Already paying for two other tools. Caved anyway. Summaries are sharper, speaker labels actually right, action items hit our Slack channel before I leave the meeting room. I don't know how I worked without this.
We evaluated five vendors. Asked all of them the same questions about webhooks, signed callbacks, behavior under load. Orpheus answered every single one without hand-waving. Months in, the platform is more stable than half our internal services. Recommended.
Needed something that could process compliance recordings without us losing sleep over data residency. The Orpheus team walked us through their security posture in detail and held to every claim during pilot. Auditors have stopped flagging the transcription pipeline as a risk. That is the bar.
Try it before you decide. The homepage tool needs no signup, 90 seconds per clip, 5 clips per day. Sign up free and your account gets 50 credits, no credit card. Paid plans from $9/month.
Transcription is just the starting point. Orpheus ships with an AI Agent. Drop a recording in and it will translate in real time (100+ languages), write summaries, extract action items and decisions, identify speakers, answer questions about the transcript, and trigger workflows by voice. Developers can wire the full Agent stack into their own product via API. Real-time streaming is coming soon for Enterprise.
Audio: MP3 / WAV / M4A / FLAC / OGG / WEBM. Video (MP4) works too. 100+ languages with auto-detection. No manual selection needed (handles code-switching and heavy accents).
Yes. Studio ($19/month) and up include the full REST API. External token integrations use async jobs with HMAC-signed webhooks or polling. Docs at /docs.
About 95%+ on mixed-language audio. Above 98% on single-language clips (pure Chinese, pure English, etc).
Audio is processed by named subprocessors (OpenAI, Google, Microsoft Azure, Deepgram, AssemblyAI, AWS Transcribe) for transcription only. Contractually none of them may use your audio for model training, and Orpheus deletes audio from our storage after the job completes. Enterprise plans add region-pinned deployments and HIPAA / SOC 2 / GDPR paperwork (BAA / DPA).
Up to about 30 hours per file. A 1-hour recording typically returns in under 2 minutes.
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