The Cursor for Product Management

Stop guessing what to build.
Let your customers decide.

Mero connects to your customer calls, support tickets, and usage data and outputs ranked feature bets with full specs your engineering team can act on. In under 60 seconds.

✓ Free to start ✓ No credit card

You have the data.
You just can't read all of it.

200 support tickets. 40 Fireflies transcripts. Usage data in Mixpanel. Churn notes in Intercom. Backlog requests in Linear.

The information to make the right decision exists. It's spread across 6 tools and nobody has time to synthesise it.

So the loudest voice in the last sprint planning wins. Again.

How it works

From signal to spec in 60 seconds

The four-step loop

01

Connect your sources

Authorize your tools once

OAuth or API key connection to Notion, Linear, JIRA, Confluence, Intercom, Fireflies, Slack, Mixpanel, PostHog, Amplitude, and GitHub. Takes 2 minutes per integration.

Mero reads: pages and databases (Notion), issues and sprints (Linear/JIRA), support conversations and churn reasons (Intercom), call transcripts and action items (Fireflies), channel discussions (Slack), usage events and funnel drops (Mixpanel/PostHog/Amplitude), and open PRs (GitHub).

Notion Linear JIRA Confluence Intercom Fireflies Slack +4 more
02

Generate insights

Click once. Get ranked bets.

Mero reads every connected source, applies recency weighting (signals from the last 30 days carry more weight than older ones), cross-references against what your team is actively building in Linear or JIRA, and generates 3 to 5 ranked feature bets.

Each bet includes: why it matters, user impact, evidence cited from your actual data, confidence level (high/medium/low), and timing (Immediate / This Sprint / Next Sprint).

High

Confidence

Medium

Confidence

Low

Confidence

03

Read the spec

Not a vague suggestion. A build brief.

Each recommendation ships with a full product spec. Specific UI changes (which screen, what changes). Data model changes (which table, what columns). Workflow changes (what triggers what). This is what you hand to an engineer, not what you take into another meeting.

// Example spec output

UI: Add progress indicator to import modal.

    Show file size limit before upload starts.

Data: Add import_error_type column to

      onboarding_events table.

Flow: Auto-trigger support ping if import

      fails after 2 retries.

04

Hand off to your team

Mero is the front end of your AI dev pipeline

Export directly to Linear (creates a fully-described issue), Notion (creates a page), or JIRA. Or click "Copy for AI Agent" to get a Cursor/Claude Code prompt with the full spec and task breakdown pre-formatted.

Cursor builds the thing. Mero decides what the thing is. That's the full loop.

Works with everything your team already uses

Notion Notion Linear Linear JIRA JIRA Confluence Confluence Intercom Intercom Fireflies Fireflies Slack Slack Amplitude Amplitude Mixpanel Mixpanel PostHog PostHog GitHub GitHub

More integrations added on request. Tell us what you use.

Decision memory

Why Mero gets smarter over time

Every run stores what was recommended. The next run, before surfacing anything, Mero checks what's in Linear/JIRA as active work. It won't recommend something you're already building. It flags if a recommendation repeats. It shows you timing badges so you know what to act on now vs. next sprint.

It's the difference between a consultant who starts fresh every meeting and one who remembers every conversation you've had for the past year.

Get early access

⚡ Immediate

Act on this now. High confidence, not in active work, directly affects current sprint goal.

🏃 This Sprint

Strong signal, plan it in. Enough evidence to justify sprint commitment.

📋 Next Sprint

Worth tracking. Not urgent enough for now but should not disappear from view.

⚠️ Overlaps with active work

This overlaps with something already in your sprint. Review before adding scope.

Sample output

What a recommendation looks like

mero / insight #1 of 4
#1 RANKED High confidence ⚡ Immediate

Fix onboarding drop-off at workspace import step

Why it matters

18 of your last 42 customer calls mention confusion at the workspace import step. It's the single highest-cited friction point in the last 30 days.

User impact

Fixing this could unblock ~40% of trials that stall in week one.

Evidence

"I got stuck on the import and just gave up" - Rhea T., call 14 Feb
Support ticket #8241: workspace import fails silently on CSV over 5MB
Slack #support: 6 variations of the same import question in 2 weeks

Spec

UI: Add progress indicator to import modal. Show file size limit before upload.

Data: Add import_error_type column to onboarding_events table.

Workflow: Auto-trigger support ping if import fails after 2 retries.

Tasks

☐ Add progress bar to ImportModal component (S, frontend)

☐ Add file size validation before upload (S, frontend)

☐ Add import_error_type to DB schema (S, backend)

☐ Write support auto-ping trigger (M, backend)

Live in early beta

Connect your tools. Get ranked feature bets with full specs in 60 seconds.

Free during beta. Paid plans coming soon. Your feedback directly shapes the roadmap - help us build the backlog you actually want.

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Got feedback or an idea for the backlog? Email us at hello@withmero.com - we read every message.