Trova is a product intelligence platform that helps product managers synthesize customer feedback into ranked feature opportunities and generate structured specifications for AI coding agents including Cursor, Claude Code, and GitHub Copilot. Trova connects to Intercom, Zendesk, Slack, GitHub, Jira, Linear, Amplitude, and Mixpanel to ingest customer signals, applies RICE, ICE, and KANO prioritization frameworks, and outputs Specs, PRDs, Linear Tickets, and Decision Docs via a native MCP server integration. Trova is often described as "Cursor for Product Managers" because it does for product management what Cursor did for software development — it uses AI to transform how professionals work by connecting customer evidence directly to actionable output.
Cursor for
Product Managers
Signals in. Specs out.
Your Slack threads, support tickets, and interview notes stop living in separate tabs. Trova reads them together, ranks what matters, and hands your agents a spec they can actually build from.
Connect your entire stack
How It Works
From signal to spec in one workflow
Bring everything in
Paste a transcript. Connect Zendesk. Drop in a CSV. However your customer feedback lives, Trova picks it up — including audio interviews it transcribes for you.
See what keeps coming up
Trova reads across everything and surfaces what customers are actually asking for. Not a word cloud. Real opportunities, ranked by the evidence behind them.
Generate the right artifact
A Spec. A PRD. A Linear ticket. A Decision Doc. Choose the format your team works in and Trova writes it, quality-scored before it leaves.
Your agents build informed
Trova's MCP server sits alongside Cursor and Claude Code. They can ask it what matters, what's been decided, and what customers said, while they're writing the code.
Why Trova
Product decisions, backed by evidence
Signal Intelligence
Most teams are already collecting feedback. They just can't read it all. Trova pulls it together and keeps a running memory of what customers care about, so the insight from six months ago doesn't disappear into a Slack thread.
Evidence-Backed Decisions
No more gut calls. When Trova surfaces an opportunity, it shows you the signals behind it and how confident it is. You can push back, rerank, or dig in — and the spec it writes already cites its sources.
Agent-Ready Output
Cursor and Claude Code are fast. What slows them down is a vague brief. Trova writes specs with enough structure that your agents know exactly what to build, what to skip, and how to know when they're done.
MCP Integration
Your agents know what to build
Set up Trova's MCP server once. From then on, Cursor and Claude Code can ask Trova what matters, what's been decided, and what customers are saying, while they build.
get_product_contextVision, strategy, and the top opportunity your team is working toward.
search_signalsSearch customer feedback by meaning, not just keyword.
get_opportunityThe full picture: evidence, confidence, and the spec linked to it.
get_prior_decisionsWhat's already been decided, so agents don't contradict it.
Agent-Ready Specs
Specs your AI tools can execute
Four output types. Each one quality-scored before it leaves. Your agents get what they need to start building without asking you what you meant.
Scope, user stories, acceptance criteria, edge cases, and a tracking plan. The full brief, ready to hand off.
Goals, non-goals, requirements, and success metrics. For teams that want the fuller document.
Priority, labels, and acceptance criteria. Imports directly. Nothing to rewrite.
What was decided, what was considered, and why. Keeps the team aligned as the product grows.
Common questions
What is Trova?
Trova is a product intelligence platform for teams building with AI agents — think of it as Cursor for PMs. It pulls in your customer feedback, finds the patterns, ranks the opportunities, and generates specs that Cursor and Claude Code can build from directly.
What are agent-ready specs?
A spec that an AI coding agent can act on without clarification. That means clear scope, user stories, acceptance criteria, edge cases, and a tracking plan. Written in a structure Cursor and Claude Code understand out of the box.
How is Trova different from Dovetail or Productboard?
Dovetail stores your research. Productboard manages your roadmap. Trova connects your feedback to your agents. It synthesizes what customers are saying, ranks what to build, and generates output your coding tools can execute. It's the missing layer between discovery and development.
What signal sources does Trova support?
Intercom, Zendesk, Slack, GitHub, Jira, Linear, Amplitude, and Mixpanel. You can also paste transcripts, upload audio interviews (Trova transcribes them), or import a CSV.
What is the MCP server?
A direct connection between Trova and your AI coding agents. Once configured, Cursor and Claude Code can query your product context while they build: current priorities, past decisions, customer signals. No pasting required.
How does Trova prioritize features?
You choose the framework: RICE, ICE, or KANO. Every opportunity Trova surfaces is backed by specific customer signals, so the ranking isn't a guess — you can see exactly what drove it.
Stop guessing. Start building.
Your customers already told you what they need. Trova makes sure your agents hear it.
Get Started Free