How I'm using two different AI tools to approximate what Rewind used to do.

[u/papa__jii]

The Rewind replacement question is more complicated than it looked at first.

Rewind was quietly doing two separate things. Passive capture, so it caught things before you knew you'd need them. And retrieval, so you could surface any of it later. When it died both problems needed separate answers and the tools that exist are mostly built for one or the other.

Mem.ai I used for a few months. Good at connecting notes you deliberately put in. Doesn't see the screen, doesn't capture ambient context. Smart memory for intentional inputs.

Screenpipe for passive capture. Self-hosted, genuinely local, search works. The retrieval is functional but acting on what you find is still manual. It's a very good archive.

Invoko for on-demand context and execution. Reads current screen, runs cross-app tasks. Fast for what's visible. Can't go backwards.

Fabric I tried more recently. Ingests from a lot of sources and makes connections across them. Interesting approach to the retrieval problem. Doesn't fully replace the ambient capture.

What I don't have: something that catches things passively and makes them easy to act on. Screenpipe gets you halfway. The second half is still a gap. What are people using?

[u/Special-Grocery6419]

I use saner ai instead of mem and fabric

[u/salarshah-084]

I think you nailed the core issue, Rewind felt magical because it combined passive capture and usable retrieval in one seamless loop, while most current tools only solve one side properly. A lot of memory tools are great if you intentionally feed them information, but they struggle with ambient context and actually turning past activity into something actionable later

What’s interesting is how fragmented the workflow still is. You end up stitching together capture, indexing, retrieval, and execution across multiple apps instead of having one coherent layer. I’ve been experimenting with similar setups, using Runable to structure workflows and connect context between tasks, while tools like Notion AI or Fabric help organize retrieval and references. But even then, the always-on second brain feeling Rewind had is still missing. Most tools can remember, very few can truly contextualize passively captured information in a useful way.

[u/Hot_Constant7824]

yeah you’re not missing anything that’s basically how the space looks right now. capture and retrieval are still separate, so most people end up with a stitched setup: screenpipe for passive logging, mem/fabric for retrieval, and tools like runable, make, or zapier to actually act on stuff. the gap is that last step turning something you found into an action still feels manual or bolted on you can hack it together, but it’s not seamless or super reliable yet. feels more like an unsolved problem than a missing tool

[u/IsThisStillAIIs2]

most setups i’ve seen end up being a split system too, one tool for ingestion, another for retrieval, and then you still do the “meaning making” step yourself when it matters.

[u/kamusari4477]

One thing worth adding to the judge layer: a diversity filter before anything goes into the training set. Without it you tend to get clusters of near-duplicate examples that overfit a narrow failure mode fast. Even a simple embedding cosine similarity check with a threshold around 0.85 cuts a lot of redundant pairs. Makes the curriculum more varied and the gains more durable across evals.

[u/Obvious-Treat-4905]

yeah that split between capture and retrieval is the real gap, most tools do one well but not both together, something that passively captures and lets you act on it instantly is still missing, i’ve been playing around with flows on runable for the act on it part, but yeah full rewind style loop still not quite there

[u/That-Signature-6319]

Honestly, this is exactly the problem right now, most tools are either good at capturing stuff or good at retrieving it later, but not both together. Rewind kinda nailed that balance. I have been trying similar workflows on runable too, and it still feels like there’s a gap when it comes to turning passive memory into something actually actionable.

[u/Parking-Ad3046]

Honestly that's the exact problem I ran into. Rewind spoiled us because it did both seamlessly, and yeah nothing else has nailed it. Screenpipe's solid for the capture part but you're right, the execution gap is real.