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FastRecall
Context across AI models. Cheap and lightning fast.
Nobody wants to be locked into a single AI model. With routers and multi-agent systems becoming essential infrastructure, your context should move seamlessly between models and providers. Existing memory solutions are overcomplicated, slow, and expensive. FastRecall starts at just $2/month, with a free sandbox available for one week. Try it out today!
Hi everyone! After working on memory at OpenAI, I built FastRecall to solve one problem: using different AI models results in clunky ad-hoc context management systems or lost context entirely. With the model layer becoming commoditized, your context should travel seamlessly across models whether you are using OpenRouter or some other model aggregator.
FastRecall offers a simple API that stores your context cheaply and efficiently. In fact, we are so cheap that recalls are entirely free, with generous plans starting at only $2/month!
If you use the same model again, FastRecall respects provider caching to save you inference costs. We also have SOTA model-free compaction of context with FlashCompact, in case you don't need full-fidelity context.
Try it today, and let me know what you think!
About FastRecall on Product Hunt
“Context across AI models. Cheap and lightning fast.”
FastRecall was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #77 on the daily leaderboard. Nobody wants to be locked into a single AI model. With routers and multi-agent systems becoming essential infrastructure, your context should move seamlessly between models and providers. Existing memory solutions are overcomplicated, slow, and expensive. FastRecall starts at just $2/month, with a free sandbox available for one week. Try it out today!
On the analytics side, FastRecall competes within Developer Tools, Artificial Intelligence and Tech — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how FastRecall performed against the three products that launched closest to it on the same day.
Who hunted FastRecall?
FastRecall was hunted by Thompson Rose. 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 FastRecall including community comment highlights and product details, visit the product overview.
Thompson Rose
Hi everyone! After working on memory at OpenAI, I built FastRecall to solve one problem: using different AI models results in clunky ad-hoc context management systems or lost context entirely. With the model layer becoming commoditized, your context should travel seamlessly across models whether you are using OpenRouter or some other model aggregator.
FastRecall offers a simple API that stores your context cheaply and efficiently. In fact, we are so cheap that recalls are entirely free, with generous plans starting at only $2/month!
If you use the same model again, FastRecall respects provider caching to save you inference costs. We also have SOTA model-free compaction of context with FlashCompact, in case you don't need full-fidelity context.
Try it today, and let me know what you think!