Aurelius: Research repository and insights platform for tagging interview data, surfacing themes, and keeping qualitative insights discoverable over time. Koji: AI-native customer research platform whose AI interviewer runs voice and text discovery conversations at scale, then synthesizes themes automatically. The right pick comes down to team size, budget, and the workflows you want to automate.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Aurelius when organizing and tagging interview transcripts and notes matters most, and Koji when building personas and validating early product concepts at scale 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.
AI-native customer research platform whose AI interviewer runs voice and text discovery conversations at scale, then synthesizes themes automatically.
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
Koji is an AI-native customer research platform built around an AI interviewer that conducts natural, in-depth conversations with research participants at scale, removing the need to schedule and moderate live discovery calls one at a time. Teams describe what they want to learn, and an AI research agent helps define goals and generate an interview guide. The AI then runs the interviews asynchronously in either a text chat or spoken voice format, asking adaptive follow-up questions and probing for depth as a human moderator would. Each completed conversation is analyzed automatically for key moments and sentiment, and findings are synthesized across all interviews into study-wide reports surfacing themes, patterns, and recommendations, with every insight traceable back to the participant quote that supports it rather than presented as a black-box summary. Koji is used for exploratory work such as discovery, persona development, and market strategy, as well as concept and messaging testing. The product is operated from Amsterdam with EU data residency and GDPR compliance, offers a freemium entry point, and integrates with tools including Claude, ChatGPT, Cursor, and Notion via an MCP server. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Aurelius is a free tier with paid upgrades (freemium); Koji is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Aurelius | Koji |
|---|---|---|
| Core capability | Centralized repository for interview notes and transcripts | Insights traceable back to specific participant quotes |
| Standout feature | Data tagging and note organization | AI interviewer that runs asynchronous voice and text discovery conversations at scale |
| Team usage | Theme and pattern identification across research | AI research agent that drafts research goals and interview guides from a brief |
| Integrations | Insight creation and report generation | Automatic per-interview analysis with key moments and sentiment |
| Languages & capture | Consistent taxonomy across projects for large repositories | Cross-interview synthesis into study-wide themes, patterns, and recommendations |
| Best-fit workflow | Multi-team collaboration with research history and archival | MCP integrations with Claude, ChatGPT, Cursor, and Notion |
Aurelius
Choose Aurelius if you need organizing and tagging interview transcripts and notes — strengths include keeps interview insights discoverable and reusable over time.
Koji
Choose Koji if you need running exploratory discovery interviews without scheduling live calls — strengths include removes scheduling overhead by running many interviews in parallel and asynchronously.
Aurelius
Koji
It depends on your workflow. Aurelius is strong for organizing and tagging interview transcripts and notes, while Koji is strong for running exploratory discovery interviews without scheduling live calls. Both transcribe and summarize meetings.
Aurelius is a free tier with paid upgrades and Koji is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Sure. Running both makes sense when their strengths don't overlap and the budget allows.
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