This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
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.
A solid foundation for anyone who wants durable agents without giving up control of their data. One thing that would make it way more useful for me: a built-in dashboard showing live workflow state and a replay button right from the UI, so I can inspect where a stuck job actually died instead of digging through Temporal logs.
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.
AEGIS was featured in Productivity (656.2k followers), Developer Tools (515.9k followers), Artificial Intelligence (473.7k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 354.5k products, making this a competitive space to launch in.
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.
Want to see how AEGIS stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Mohammed Arshad Ansari