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AEGIS
Self-hosted AI agents that interrupt you less
AEGIS is a self-hosted platform where named agents run durable Temporal workflows over your own data - tasks, money, knowledge, homelab alerts - and only ask for a decision when they truly need one. Local-LLM-first, MIT-licensed. Fork it and make it yours.
Hey Product Hunt I'm Arshad.
I built AEGIS over the past year to run my own life — tasks, email, money, a knowledge base, and my homelab — and open-sourced it last week (MIT).
The idea: not another assistant to check, but a system that handles the boring parts quietly and only interrupts me when a decision is genuinely mine. A small fleet of named agents run durable Temporal workflows over my own data; every human-in-the-loop
moment is one primitive (a Postgres row + a chat card + a workflow that waits for my tap). It's local-LLM-first through a LiteLLM proxy, reaching for a hosted model only when a job needs it.
What it's not: it's not a SaaS (no hosted version — you bring your own credentials and models), and it's not a framework to build on. It's a complete app you fork and configure for your own life.
I'd love feedback from people who've tried to wire agents into their real day — especially on the single-interruption-primitive model and running this on local models. Happy to answer anything.
About AEGIS on Product Hunt
“Self-hosted AI agents that interrupt you less”
AEGIS was submitted on Product Hunt and earned 9 upvotes and 3 comments, placing #151 on the daily leaderboard. AEGIS is a self-hosted platform where named agents run durable Temporal workflows over your own data - tasks, money, knowledge, homelab alerts - and only ask for a decision when they truly need one. Local-LLM-first, MIT-licensed. Fork it and make it yours.
On the analytics side, AEGIS competes within Productivity, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how AEGIS performed against the three products that launched closest to it on the same day.
Who hunted AEGIS?
AEGIS was hunted by Mohammed Arshad Ansari. 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.
For a complete overview of AEGIS including community comment highlights and product details, visit the product overview.
Mohammed Arshad Ansari