Customer feedback platform
A customer feedback platform for software companies: users post and vote on ideas, follow a public roadmap, and the team gets AI summaries.
Malto.io admin and marketing site
01 Overview
Malto.io is a customer feedback platform for software companies. Customers post ideas on a public board, vote on what they want and follow each request through a public roadmap and changelog. The product team gets an admin console with AI summaries, sentiment scoring and bulk intake.
Software teams hear from users everywhere, but that input rarely lands in one place in a form anyone can act on. Malto gives each company one board where requests are grouped, ranked by real votes and answered in public. We built the marketing site, the customer board, the admin console and the API.
02 The challenge
Feedback was arriving faster than teams could sort it, and customers had no idea what happened to their ideas.
Feature requests came in by email, chat, support tickets and sales calls, and the same idea arrived ten times under ten titles.
Votes had to come from signed-in people and count only once, or the ranking meant nothing.
Customers wanted to hear when an idea changed status, and a decline needed a written reason.
The team had far more comment text than anyone had time to read.
03 What we built
We built a Next.js and TypeScript front end on a Node.js and MongoDB API, with a public board, roadmap and changelog for each company and an admin console with AI tools.
Customers post ideas, vote, react and comment, with columns for Open, Under Review, Planned and In Progress. Everyone can see what has real support behind it.
A text search flags likely duplicates as people write a new request. Votes land on the existing idea instead of splitting across copies.
Admins move requests between Planned, In Progress and Completed. Voters are notified automatically when a request they backed changes status.
Release notes link back to the request that shipped, and the users who asked for it get notified. This closes the loop with the people who spoke up.
Anthropic models write a weekly summary of new requests, votes and shifts in demand, with suggested next steps. The team gets the picture without reading every comment.
Feedback is scored for sentiment and grouped by category, so the team can see how users feel about performance, pricing or a recent release.
Admins paste text from a call or a ticket, and the AI splits it into separate requests. Feedback from outside the board still gets counted.
Admins change status, merge duplicates, assign teammates and keep internal notes, with a full history on each request.
04 The results
Malto now runs a public site, a customer board, an admin console and an API that work together.
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