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Perplexity Computer streamlines enterprise workflows by harnessing AI agents that automate tasks and integrate tools, offering unprecedented efficiency and cost savings for businesses.
Perplexity Computer, an AI orchestrator that manages a team of AI agents on your behalf, has made significant strides since its inception. Initially developed as an internal tool at Perplexity, it quickly evolved into a powerful enterprise solution. The system codes in Claude Code and GPT Codex, performs deep research, orchestrates tools across 400+ connectors, creates files, and more-all on a secure server with reversible actions.
In the first two weeks of limited availability, Computer saved Perplexity Max subscribers over $91M, according to benchmarks compiled from McKinsey, Harvard, MIT, and BCG and Nielsen. Since then, it has performed over $776M in labor-equivalent work for Perplexity Enterprise, Pro, and Max subscribers.
The earliest version of Computer lived in a shared Slack channel at Perplexity. Initially dubbed ASI (a play on artificial superintelligence and “a Slack integration”), it allowed users to tag ASI and ask it to perform any task imaginable-pulling data from Snowflake, researching the web, preparing board memos, writing code, and more.
One of the key strengths of Computer is how it keeps the request, context, and output together in Slack. This transparency fosters collaboration:

In Slack, Computer can handle a wide range of tasks:
For example, users can ask Computer to:
Perplexity Computer’s integration into Slack has revolutionized how teams collaborate and execute tasks. By keeping everything in one place, it enhances transparency, efficiency, and productivity. As the technology continues to evolve, its impact on collaborative workflows is likely to grow even further.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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2 April 2026
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