Pipali is an AI coworker that lives on your computer. It interacts with your files, browser and apps to get real work done. Pipali can handle most computer work — deep research, polished docs, browser tasks and routine errands. Teach it your workflows with Skills, run recurring tasks with Routines and integrate with your apps like Linear, Slack and GitHub via MCP.
We built Pipali because we wanted AI to move beyond chat — not just answer questions, but actually operate your computer with you and finish useful work.
Pipali is a desktop AI coworker that can:
research across your files and the web
create briefs, spreadsheets, emails, reports, and personal apps,
run recurring tasks, react quickly to events (from releases to stock prices)
interact with your apps via MCP
work asynchronously and notify you when it needs help
stay safe with sandboxing, permissions, and explicit confirmations
It already helps folks manage investments, generate leads, publish apps and plan sprints.
Things to try:
Draft a weekly project update from your notes, Linear, and Slack
Create a personal newspaper from today’s top stories
Create investor update from your product metrics on PostHog
Optimize your finances from your bank statements or Bank MCP
The Skills + Routines concept is spot on. Every AI agent I've tried is great for a single task but can't repeat it reliably. Having a way to codify workflows and run them on schedule is where the real productivity gains are. How does Pipali handle multi-step browser tasks - does it use the DOM or computer vision?
The isolated chrome profile solution for app conflicts is cleaner than i expected. one gap i'm thinking about: for the event-driven routines, is triggering polling-based or can it hook into actual webhooks? if it's polling, the latency on reacting to something like a github release could make the whole "react quickly to events" claim feel sluggish.
kinda interesting that you focused on actual computer workflows instead of just chat ux. the github +slack + linear integrations make it feel more useful for real work tbh. would love to see how people end up using skills after a few weeks.
The async operation model is what separates this from a lot of screen-recording “agents” that still need you to supervise every step. Most desktop agents feel more like remote control with extra AI layers - Pipali running tasks in the background and only notifying you when intervention is needed feels much closer to a real coworker workflow. We tested a competing tool recently and abandoned it because it locked up a machine for nearly 20 minutes while “observing” the workflow. One question: is the event reaction system primarily polling-based, or does it support webhook/event-driven triggers for integrations?
"Any computer work" is a big claim curious what it handles best in practice. Is it more of a task automation tool or does it reason through multi-step problems?
Most desktop agents I've seen treat every task like it's starting from scratch — no memory of how you handled something last Tuesday. The Skills feature is the first time I've seen that actually addressed properly. What I'm curious about is how it deals with apps that don't have clean MCP support yet — does it fall back to something like computer use or just fail gracefully
I like that Skills and Routines solve the recurring problem where most AI agents are great once but break on the second run. I'm curious as to how Pipali handles conflicts when a Routine triggers while you're actively using the same app it needs to control?
About Pipali on Product Hunt
“An AI coworker for any computer work”
Pipali launched on Product Hunt on May 13th, 2026 and earned 121 upvotes and 14 comments, placing #11 on the daily leaderboard. Pipali is an AI coworker that lives on your computer. It interacts with your files, browser and apps to get real work done. Pipali can handle most computer work — deep research, polished docs, browser tasks and routine errands. Teach it your workflows with Skills, run recurring tasks with Routines and integrate with your apps like Linear, Slack and GitHub via MCP.
Pipali was featured in Productivity (651.7k followers), Open Source (68.4k followers), Artificial Intelligence (468.5k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 258.6k products, making this a competitive space to launch in.
Who hunted Pipali?
Pipali was hunted by Debanjum. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Pipali stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Debanjum
Hey Product Hunt 👋,
We built Pipali because we wanted AI to move beyond chat — not just answer questions, but actually operate your computer with you and finish useful work.
Pipali is a desktop AI coworker that can:
research across your files and the web
create briefs, spreadsheets, emails, reports, and personal apps,
run recurring tasks, react quickly to events (from releases to stock prices)
interact with your apps via MCP
work asynchronously and notify you when it needs help
stay safe with sandboxing, permissions, and explicit confirmations
It already helps folks manage investments, generate leads, publish apps and plan sprints.
Things to try:
Draft a weekly project update from your notes, Linear, and Slack
Create a personal newspaper from today’s top stories
Create investor update from your product metrics on PostHog
Optimize your finances from your bank statements or Bank MCP
P.S. We're open-source! Check us out on GitHub: https://github.com/khoj-ai/pipali
We’d love your feedback — especially: what work would you actually delegate to an AI coworker running on your own computer?