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Solaris
Archive what happened. Believe. Know the difference.
Solaris is long-term AI memory built for honesty, not just recall. It keeps an append-only archive as source truth, derives structured memory cautiously, and uses editorial review to decide what becomes enduring memory. It also surfaces divergence between current belief and historical record, supports graph-aware retrieval, and can run in shadow mode beside an existing system before becoming authoritative.
I built Solaris because most AI memory feels either fuzzy, forgetful, or impossible to inspect.
Solaris takes a different path: keep the archive, derive structure cautiously, remember selectively through editorial review, and make divergence between current belief and historical record visible instead of hiding it.
It’s open source, early, and meant for builders working on long-lived agents, assistants, and memory systems.
Would especially love feedback on:
archive vs belief separation
shadow-mode adoption beside an existing system
graph and pattern memory without overclaiming
Happy to answer anything openly.
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About Solaris on Product Hunt
“Archive what happened. Believe. Know the difference.”
Solaris was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #158 on the daily leaderboard. Solaris is long-term AI memory built for honesty, not just recall. It keeps an append-only archive as source truth, derives structured memory cautiously, and uses editorial review to decide what becomes enduring memory. It also surfaces divergence between current belief and historical record, supports graph-aware retrieval, and can run in shadow mode beside an existing system before becoming authoritative.
Solaris was featured in Open Source (68.4k followers), Developer Tools (511.7k followers), Artificial Intelligence (467.3k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 188.2k products, making this a competitive space to launch in.
Who hunted Solaris?
Solaris was hunted by Yonas Biniam. 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.
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Yonas Biniam