Aurelius: Research repository and insights platform for tagging interview data, surfacing themes, and keeping qualitative insights discoverable over time. Scriberr: Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript. Here's where each one pulls ahead on pricing, features, and the meetings it suits best.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Aurelius when organizing and tagging interview transcripts and notes matters most, and Scriberr when researchers and journalists generating diarized transcripts of recorded conversations matters most. Try them side by side on real calls before deciding — needs vary by team.
Research repository and insights platform for tagging interview data, surfacing themes, and keeping qualitative insights discoverable over time.
Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript.
Aurelius is a research repository and insights platform designed for UX researchers, designers, and product teams to manage qualitative research data end to end. It sits between a note-taking tool and a full research repository: teams bring in raw data such as interview notes and transcripts, organize and tag it, and the tool surfaces patterns and helps create reusable insights over time. Core capabilities include centralized storage for research data, note organization, data tagging, theme and pattern identification, and report generation, so findings can be referenced long after a study concludes. Aurelius is built with larger research organizations in mind, supporting consistent taxonomy across projects and keeping insights discoverable as repositories grow, while also enabling multi-team collaboration and research history and archival features. Researchers describe it as a low-effort way to tag and create insights they can reference in later product discussions. The platform positions itself as an alternative to fragmented approaches that rely on spreadsheets, Confluence, or Airtable for storing research. By centralizing qualitative data and making it searchable and well-organized, Aurelius aims to ensure that interview insights remain accessible and actionable across an organization. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Scriberr is an open-source, self-hosted audio transcription application aimed at people who want to keep recordings and transcripts on their own hardware. It uses the open-source Whisper family of models (via the WhisperX engine) to transcribe audio and video files entirely offline, with no requirement to send data to a cloud provider. The project is distributed under the MIT license and is packaged as a single binary, with a Go backend and a Svelte frontend compiled into the binary, while Python handles the underlying AI transcription. Beyond raw transcription, Scriberr can automatically detect and label different speakers (diarization), generate summaries using custom prompts, and let users chat with a transcript by connecting to Ollama or OpenAI-compatible providers. It includes a transcript reader with playback follow-along and seek-from-text, a built-in audio recorder, note-taking, and a folder watcher plus API endpoints for automation and integration with tools like n8n. The maintainer publicly noted development is paused but not abandoned, and community contributions are welcome; the most recent release at the time of review was v1.2.0 in December 2025. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Aurelius is a free tier with paid upgrades (freemium); Scriberr is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Aurelius | Scriberr |
|---|---|---|
| Core capability | Centralized repository for interview notes and transcripts | Local, offline transcription using Whisper models via the WhisperX engine |
| Standout feature | Data tagging and note organization | Automatic speaker diarization (who said what) |
| Team usage | Theme and pattern identification across research | AI summaries with custom prompts via Ollama or OpenAI-compatible providers |
| Integrations | Insight creation and report generation | Chat with your transcripts to ask questions and pull insights |
| Languages & capture | Consistent taxonomy across projects for large repositories | Built-in audio recorder and note-taking on transcripts |
| Best-fit workflow | Multi-team collaboration with research history and archival | Folder watcher and API endpoints for automation workflows |
Aurelius
Choose Aurelius if you need organizing and tagging interview transcripts and notes — strengths include keeps interview insights discoverable and reusable over time.
Scriberr
Choose Scriberr if you need privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure — strengths include fully self-hosted and offline, keeping audio and transcripts on your own hardware.
Aurelius
Scriberr
It depends on your workflow. Aurelius is strong for organizing and tagging interview transcripts and notes, while Scriberr is strong for privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure. Both transcribe and summarize meetings.
Aurelius is a free tier with paid upgrades and Scriberr is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Often yes: teams combine tools when one handles capture and another handles analysis.
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