How are you planing to segregate between professional use and personal use, I dont want any agent or any llm to know all the time what i have been doing on my system, it would be privacy nightmare and most of the time the screencapture is not meaningful. People may use their work laptop or devices to checkout reddit or hackernews occasionally.
Funny timing. I've been building something similar in my spare time called Daydream. There’s a lot of overlap: local screen/audio capture, OCR and transcription, window and activity context, SQLite, and a searchable memory of what happened.
The main difference is the product direction. Screenpipe seems focused on continuously giving agents context through APIs, MCP, and skills. Daydream is more narrowly built around answering "what did I do today?" through a timeline you can inspect, replay, search, and turn into a daily digest.
I'm also treating deletion as part of the data model. If you cut a sensitive span, its frames, audio, OCR, transcripts, embeddings, and summaries should be deleted or invalidated too.
Mine is still early and Linux-first. I'm open-sourcing it in case anyone wants to contribute, poke around, or use it as a starting point. It’s built with Tauri, a Rust backend, React/TypeScript, SQLite, GStreamer, Whisper, OCR, and VLM processing.
I genuinely didn’t know you were building this when I started. Apparently personal memory capture is becoming a SaaS category too lol.
I tried this ~ a week ago, tried one of the suggested automations and it pretty immediately started sending my local api keys to an endpoint… afk right now but can share more when I’m back
Been a user of Screenpipe to build some "Ai-buddies" for me since last year. Core of that is giving AI a look at what is happening in time space. Without Screenpipe this was rather hard to do at the performance screenpipe gives.
You had my interest until "source available". Especially when you used MIT from the start and changed it later. FOSS hackers like me feel betrayed by moves like that because your product was built on FOSS others created and you are not paying that forward.
Also, I for one would never invest a second in tools I cannot freely modify and share the code of under OSI terms. I would strongly suggest a convenience tax model. Hackers will self host and maybe contribute but those with more money than time will put in a credit card. Maybe offer end to end encrypted memory and compute to secure enclaves where additional compute on the data can be done when the laptop is closed. (Shameless plug, this is what https://caution.co enables, and 100% FOSS)
However, with "source available" you are just begging for someone to AI launder your code into a FOSS clone you will have 0 recourse on. If you FOSS it yourself then you get to capture the FOSS community destined to form around this idea. Some of that community will have bosses that will pay you.
MIT may not be the right play though. AGPL is a good middle ground as it flips the script. Corpo lawyers are allergic to AGPL and will pay for an alternative license, but for community hackers that might want to improve and recommend your code it offers no restrictions.
You can decide which AI provider you use, either local through Ollama for example, using your own cloud API key, or using Screenpipe cloud. We also support confidential inference through tinfoil.sh
Screenpipe captures accessibility tree and screenshot when you perform a meaningful action. It doesn't use AI at recording time (except PII removal and OCR infrequently). So it can be every few hundred milliseconds to few minutes or more (if screen idle or sleeping)
We usually benchmark CPU usage on $200 Windows/MacOS laptop
Implementation specifics aside, I increasingly think life and death cycles are preferable. The opposite of omnipotent context, I want cycles of clean slates so that baggage - of all kinds - does not weigh down the new.
Interesting, I partly agree. It sounds like how the human brain works, but what nature learned is not necessarily what we should keep
We capture everything and gives you and option for a flexible data retention policy, so that you can prune mp4 files for example or verbose accessibility trees, while our agents generate high level memories referencing low level data
It still not perfect, but ideally Screenpipe would record forever so that you have infinite memory of every tiny details, while having high level structured memories for humans and agents, individually or as a company
I think this is true for some tasks where you want a clean slate, but increasingly I find myself constantly referencing specific skills, or having files with prompts I use all the time. I'd much rather have an agent that remembers things about me and specifics about my workflows and "taste" - of course having the ability to reset context sometimes or prune memory is valuable but I think the future of agentic AI is blocked on "omnipotent context"
Yeah there’s a need for the distilled learnings of all past hard earned insights. But i think much of the value is in the distillation.
in my experience, even within a single project, the more agentic cycles, the more features and the more surface area the more cruft builds up. This is an obvious observation, but I suppose I’m at the point I think the move forward is to create a new project, keep only what worked from the preceding as modularized entities and intentionally wipe away all past of how we got there save for the API interface truths.
Well, i'm not sure who your customers are (except companies in Russia, NK..), but european employers would break laws by allowing your software to be used, long even before AI became a thing and especially after the EU AI Act
has passed. To put it mildly, no sane corporation would allow such software to be used which tells me a bit about the sanity of the current VC landscape.
Anything that tracks employees actions beyond high-level "are they doing their job according to the job descriptions" is forbidden by privacy laws and otherwise will be striken down by a workers council.
That's not just specific to digital stuff. E.g. warehouse cameras that film anything else beyond securing entries/exits, like they are commonplace in e.g. the US don't exist for the same reason.
and what endpoint would it use to upload those files? what's the authentication needed for those endpoints? why would everyone on earth fail to notice these exfiltration endpoints if they exist?
you're being unnecessarily hostile about a threat that almost certainly doesn't exist. And if it does, you can absolutely block those uploads before they even happen. In fact if you don't already block uploads to hosts you don't know about, then you're not really taking anything seriously, are you?
Hey sorry about that, it's been a while ago, we didn't know that emails on Github were not allowed to be used (since I received many emails from startups that way). We apologized to our users and never did this again
I don't know anything about this company and what it may or may not have done, but to be clear, the link just says that when you star their github repo, they add your email address to their marketing list.
I think that sucks, but it's certainly not what I thought of when I read your one-liner (which implies that they harvest and abuse your actual recorded data).
For one, even taking the ethos of local-only as something bulletproof, I can't think of a pro that would outweigh the con of recording everything I do. Part of that might be my lack of imagination, as I'm not a heavy user of ai besides basic Claude code.
Most important though, the concept is ripe for pivoting away from local-only. It will only take a juicy investment offer and I'm sure local-onpy will be quietly forgotten.
Thanks! In fact most of AI apps today have a screen recording component, including Claude, Codex. There are even apps used by hundred of thousands that record your screen 24/7 in the cloud, to provide context, like Screenpipe does.
We're the only local-first, open source option
How much time do you spend explaining the context to your Claude? Or writing detailed prompts? Copy pasting documents into the prompt?
Thanks, I was unaware of that. After some research, though, it seems screen capturing by Claude Code is something you need to activate yourself.
>How much time do you spend explaining the context to your Claude? Or writing detailed prompts? Copy pasting documents into the prompt?
Prompts: not much. If I feel my prompt is becoming a paragraph-long text, that's when I know I probably haven't thought things through enough yet. Documents: I typically have a interpreter console open where I'll do something like File.write("foo.html", page.body), and I'll just tell Claude to "find the missing div in foo.html". Or if its a file already in the repo, I won't need to copy paste anything. Context: also not much. It has all the context by default, doesn't it?
The main difference is the product direction. Screenpipe seems focused on continuously giving agents context through APIs, MCP, and skills. Daydream is more narrowly built around answering "what did I do today?" through a timeline you can inspect, replay, search, and turn into a daily digest.
I'm also treating deletion as part of the data model. If you cut a sensitive span, its frames, audio, OCR, transcripts, embeddings, and summaries should be deleted or invalidated too.
Mine is still early and Linux-first. I'm open-sourcing it in case anyone wants to contribute, poke around, or use it as a starting point. It’s built with Tauri, a Rust backend, React/TypeScript, SQLite, GStreamer, Whisper, OCR, and VLM processing.
I genuinely didn’t know you were building this when I started. Apparently personal memory capture is becoming a SaaS category too lol.
Code is here: https://github.com/snackbit/daydream
https://cal.com/team/screenpipe/chat
Feel free to configure local LLM like Ollama, btw
I'm curious what does your AI buddies do more specifically and how do you use them?
Also, I for one would never invest a second in tools I cannot freely modify and share the code of under OSI terms. I would strongly suggest a convenience tax model. Hackers will self host and maybe contribute but those with more money than time will put in a credit card. Maybe offer end to end encrypted memory and compute to secure enclaves where additional compute on the data can be done when the laptop is closed. (Shameless plug, this is what https://caution.co enables, and 100% FOSS)
However, with "source available" you are just begging for someone to AI launder your code into a FOSS clone you will have 0 recourse on. If you FOSS it yourself then you get to capture the FOSS community destined to form around this idea. Some of that community will have bosses that will pay you.
MIT may not be the right play though. AGPL is a good middle ground as it flips the script. Corpo lawyers are allergic to AGPL and will pay for an alternative license, but for community hackers that might want to improve and recommend your code it offers no restrictions.
We're open to more feedback, things could change in the future
Nearly everyone just pays them to run it (myself included - I self host GitLab and still pay them!).
During normal usage, how often does it try to parse info from the screen capture? Once a minute?
Screenpipe captures accessibility tree and screenshot when you perform a meaningful action. It doesn't use AI at recording time (except PII removal and OCR infrequently). So it can be every few hundred milliseconds to few minutes or more (if screen idle or sleeping)
We usually benchmark CPU usage on $200 Windows/MacOS laptop
We capture everything and gives you and option for a flexible data retention policy, so that you can prune mp4 files for example or verbose accessibility trees, while our agents generate high level memories referencing low level data
It still not perfect, but ideally Screenpipe would record forever so that you have infinite memory of every tiny details, while having high level structured memories for humans and agents, individually or as a company
in my experience, even within a single project, the more agentic cycles, the more features and the more surface area the more cruft builds up. This is an obvious observation, but I suppose I’m at the point I think the move forward is to create a new project, keep only what worked from the preceding as modularized entities and intentionally wipe away all past of how we got there save for the API interface truths.
That's not just specific to digital stuff. E.g. warehouse cameras that film anything else beyond securing entries/exits, like they are commonplace in e.g. the US don't exist for the same reason.
We also have early support for encryption at rest through our CLI
Ultimately, it’s up to you what you run and trust
Screenpipe is open source and local-first
You can inspect it and keep your data on-device, with encryption at rest
Source available *
you're being unnecessarily hostile about a threat that almost certainly doesn't exist. And if it does, you can absolutely block those uploads before they even happen. In fact if you don't already block uploads to hosts you don't know about, then you're not really taking anything seriously, are you?
if this doesn't run fully local its a no go for enterprise let alone ordinary users
https://screenpipe.com /how-to-install
I think that sucks, but it's certainly not what I thought of when I read your one-liner (which implies that they harvest and abuse your actual recorded data).
Have you ever founded a company and tried to find paying customers?
You'd probably be offended if I sent you a cute 90's era AOL CD with our software on it.
OP: I wouldn't be offended if you emailed me in this way. Ignore the naysayers. This is perfectly kosher.
In fact, I'm going to check out your company in depth just because of this pearl clutching.
Keep building and don't let naysayers tear you down over something not even slightly evil. (Venomous attacks are more evil than this, frankly.)
Please don't create accounts to break HN's rules with.
For one, even taking the ethos of local-only as something bulletproof, I can't think of a pro that would outweigh the con of recording everything I do. Part of that might be my lack of imagination, as I'm not a heavy user of ai besides basic Claude code.
Most important though, the concept is ripe for pivoting away from local-only. It will only take a juicy investment offer and I'm sure local-onpy will be quietly forgotten.
We're the only local-first, open source option
How much time do you spend explaining the context to your Claude? Or writing detailed prompts? Copy pasting documents into the prompt?
>How much time do you spend explaining the context to your Claude? Or writing detailed prompts? Copy pasting documents into the prompt?
Prompts: not much. If I feel my prompt is becoming a paragraph-long text, that's when I know I probably haven't thought things through enough yet. Documents: I typically have a interpreter console open where I'll do something like File.write("foo.html", page.body), and I'll just tell Claude to "find the missing div in foo.html". Or if its a file already in the repo, I won't need to copy paste anything. Context: also not much. It has all the context by default, doesn't it?