Trova vs Dovetail
Dovetail stores research.
Trova ships features.
Dovetail is a great research repository. But if you're building with Cursor or Claude Code, you need more than tagged insights — you need specs your agents can execute.
Feature Comparison
| Dovetail | Trova | |
|---|---|---|
| Core Purpose | Research repository — store, tag, and search qualitative data | Product intelligence — synthesize signals into ranked opportunities and agent-ready specs |
| Signal Sources | Manual uploads, interview recordings, some integrations | Intercom, Zendesk, Slack, GitHub, Jira, Linear, Amplitude, Mixpanel + audio transcription |
| Analysis | Manual tagging and highlights with AI-assisted search | Automatic synthesis across all sources with confidence-scored opportunities |
| Prioritization | None — Dovetail is a research tool, not a prioritization tool | Built-in RICE, ICE, and KANO frameworks with evidence-based ranking |
| Output | Tagged insights and reports for humans to read | Specs, PRDs, Linear tickets, Decision Docs — structured for AI coding agents |
| Agent Integration | None | Native MCP server for Cursor and Claude Code — agents query context while building |
| Best For | UX researchers who need a searchable archive of qualitative research | Product managers shipping with AI agents who need specs, not just insights |
The fundamental difference
Dovetail answers: "What did customers say?"
Trova answers: "What should we build, and here's the spec for it."
If your team is still writing specs by hand and handing them to human engineers, Dovetail might be enough. If you're shipping with AI coding agents, you need the output to be agent-ready from the start.
Use Dovetail if...
- •You're a UX research team focused on qualitative analysis
- •You need a searchable archive of interview transcripts
- •Your workflow ends at insights, not specs
- •You don't use AI coding agents
Use Trova if...
- ✓You're a PM who needs to turn feedback into shipped features
- ✓You ship with Cursor, Claude Code, or GitHub Copilot
- ✓You want prioritization built in, not bolted on
- ✓You need specs your agents can build from directly
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