Product intelligence for product teams

Drowning in feedback?Ship what matters.

Signal pulls customer voice from Slack, HubSpot, surveys, and email. AI clusters it into themes, surfaces emerging issues, and routes the right work to engineering — so your team prioritizes from signal, not opinion.

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Captures from
SlackHubSpotNPS surveysEmailNotionManual entry
The problem

Customer feedback lives in silos. The most important signals get buried.

Your customers tell you, every day, exactly what to build next. They tell you in Slack, in support tickets, in NPS comments, in sales calls. But there's no systematic way to detect emerging issues before they become crises, quantify how widespread a complaint actually is, or close the loop with the customers who told you in the first place.

How Signal helps

AI proposes. You dispose.

Every AI classification — sentiment, theme, severity, RICE — is editable. AI does the clustering at scale. PMs make the decisions that matter.

AI clusters every piece of feedback

Within 30 seconds of intake: sentiment, theme tags, severity, and bug detection. AI tags are visually distinct from manual ones until a PM confirms them.

Triage at keyboard speed

Single-key shortcuts in the Triage Queue. Confirm, flag as bug, mark noise, create opportunity — all without lifting your hands. Burn through a day of feedback in minutes.

RICE scoring you actually trust

AI suggests Reach, Impact, Confidence. You set Effort. Every score editable in any view — Kanban card, detail page, or spreadsheet table. Sort by any dimension.

Bugs route directly to engineering

Flag-as-bug opens a modal with an AI-drafted Jira ticket — title, repro steps, severity, project. Bugs skip the opportunity lifecycle so they don't get stuck in product discovery.

Watch Mode catches regressions

When you ship a fix, Signal watches the theme for 60 days. New feedback lands as post-ship signal — you'll know within minutes if the fix didn't actually solve the problem.

Close the loop with customers

When a feature ships, Signal generates a digest of every customer who reported the underlying issue. Push to Slack so CX can follow up personally — the single highest-leverage feature for closing the feedback loop.

How it works

Four steps from raw feedback to shipped feature.

01

Capture

Slack reactions, HubSpot tickets, NPS verbatims, manual entry. Signal pulls every channel.

02

Cluster

AI groups related feedback into themes within 30 seconds. Severity, sentiment, and a bug flag, all editable.

03

Triage

PMs review in keyboard-first triage. Confirm AI tags, create opportunities, route bugs to engineering.

04

Ship

Push prioritized opportunities to Jira. Watch Mode flags regressions. Loop-close notifies the customers who reported it.

What changes

Three things look different by Friday.

Mondays stop starting with the inbox.

AI clusters the weekend's feedback before you sit down. Triage takes minutes — not the morning.

Roadmap arguments end with data.

Severity, reach, impact, and the customer count for every theme. The case for each bet is already on the card.

Customers actually hear back.

When a fix ships, the people who reported it get a note — not next quarter, the same day.

Built for product teams who'd rather be shipping.

Open the demo — every page is wired, the data is realistic, the flows are honest about what's stubbed.

  • Role switcher (Submitter / PM / Admin)
  • 100+ realistic feedback items
  • Eisenhower priority matrix