Is there any chance you might support a local-first version of this in the future? I've been interested in apps like this and Littlebird in particular seems very attractive. But I'm loathe to essentially send screenshots/summaries/etc of all my activity to a cloud solution, regardless of any claims you make about encryption. Any mistake you make could be catastrophic for me, which thoroughly dominates any upside to using your product. It's a non-starter.
We will for sure, but the issue is that without local LLMs, there's no way to offer a truly fully local version. And the local LLMs are dumb. So basically, you would still need to trust the LLM providers. Totally understand that this is a deal breaker for some people, but for many users, the theoretical risk is worth it. We do regular security audits, encrypt in transit and at rest, pen tests, etc.
Um, dismissing the tech as "the local LLMs are dumb" seems shortsighted. I can run some pretty impressive models on my local Mac, but it has >64gb of ram and an M3 Max.
Given the privacy benefit I wouldn't dismiss them so fast. I'd suggest picking one or two that your prompts will work well with and treating it as "we let you run with local models too, if you have a computer capable of that." This will (a) quiet the people who complain about everything and (b) get more people to try the cloud model knowing they could move to a local model for real usage.
I'm not dismissing them. I'm saying they're not there yet. As a startup, we have to prioritize. We can't do everything simultaneously, and it would be a substantial engineering effort to have a dual architecture as well as potentially more security holes. And the amount of people that want to run local LLMs is very small. I use local LLMs when I'm on flights, and that is my personal assessment. They are all benchmark-maxed and incapable of reliable tool calling or consistency over meaningfully long conversations.
Hey, I'm Dmitriy from Littlebird. For your use case, would you want the underlying LLM to be local as well, so that your data doesn't get sent to the "big dog" LLM providers? It's an important consideration because it wouldn't be nearly as smart then - though I totally understand if that's the only way it could work for you.
I'm not the OP but I came here to voice the same concern. I would love to use something like this. I also signed up for rewind.ai and Limitless and pre-ordered the pendant. But ultimately I cancelled it out of privacy concerns.
I wonder if it could be local storage and you could provide your own Open Router endpoint? That way it could be a local model or your own deployment of GPT/Claude in Azure/Bedrock/Vertex etc where you can control retention policies etc.
Basically, I want to know that you guys don't have access to view my stuff. I get that that limits your ability to improve the product and support issues, but when I'm sending everything it really starts to matter. Just thought I'd share what held me back from immediately signing up despite really wanting to use a product like this!
Littlebird is a desktop app that remembers everything you’ve been working on. Meetings, messages, docs, browsing, etc. It helps you stay focused, prioritize, recall, and move projects forward. Unlike any product on the market today, Littlebird uses screenreading to understand all the text on screen, for all applications, without any cumbersome setup. It understands who said what, when, and keeps track of your projects in great detail. It uses that context to build a rich understanding of your life: who matters to you, what you're working on, and what you care about this week and this year. It extends your working memory and your capacity to think and create.
You control what Littlebird sees, what it remembers, and what it forgets. We designed Littlebird to be private, secure, and user-controlled by default.
The screenreading approach is genuinely clever as a distribution strategy — no integrations to maintain, no OAuth flows to break, works on day one with everything. The hard part isn't the tech though, it's the trust problem. Rewind, Limitless, and now this all hit the same wall: the people most likely to benefit from this (busy professionals with complex workflows) are exactly the people most exposed if something goes wrong. Until there's a credible local-first path, the TAM is going to stay small.
If you thought Slack logs were damning in discovery, wait til someone suing or prosecuting you figures out that everything you typed and looked at, etc., is in the cloud
Agree with this direction. Most tools assume structured inputs, but real workflows are messy and visual. Feels like screen understanding is still very underexplored compared to text.
Screenreading is a smart way to solve the integration problem. Every other tool in this space makes you connect each app one by one and you're always waiting for them to support your workflow. This just watches what you watch. Feels obvious in hindsight - cool stuff
I wish Claude cowork could get better at this. I often end up with Claude performing ad hoc tasks involving multiple windows and it’s so slow. It stops and screenshots and thinks and screenshots to confirm after entering one Google sheet cell of data for example. I’m sure it’ll get better over time.
Does your company actually look at resumes? you post in HN but nothing ever goes through. I have a feeling that your recruitment team is not doing their job properly (or being super selective)
How are you handling the data extraction? Is it a multimodal VLM (OCR+LLM) or a standard OCR engine feeding a separate LLM? I’ve been hitting a wall trying to understand how this viable. The compute overhead for real-time analysis at scale seems massive without a serious backend. How are you managing the frequency?
Is there any chance you might support a local-first version of this in the future? I've been interested in apps like this and Littlebird in particular seems very attractive. But I'm loathe to essentially send screenshots/summaries/etc of all my activity to a cloud solution, regardless of any claims you make about encryption. Any mistake you make could be catastrophic for me, which thoroughly dominates any upside to using your product. It's a non-starter.
We will for sure, but the issue is that without local LLMs, there's no way to offer a truly fully local version. And the local LLMs are dumb. So basically, you would still need to trust the LLM providers. Totally understand that this is a deal breaker for some people, but for many users, the theoretical risk is worth it. We do regular security audits, encrypt in transit and at rest, pen tests, etc.
Um, dismissing the tech as "the local LLMs are dumb" seems shortsighted. I can run some pretty impressive models on my local Mac, but it has >64gb of ram and an M3 Max.
Given the privacy benefit I wouldn't dismiss them so fast. I'd suggest picking one or two that your prompts will work well with and treating it as "we let you run with local models too, if you have a computer capable of that." This will (a) quiet the people who complain about everything and (b) get more people to try the cloud model knowing they could move to a local model for real usage.
I'm not dismissing them. I'm saying they're not there yet. As a startup, we have to prioritize. We can't do everything simultaneously, and it would be a substantial engineering effort to have a dual architecture as well as potentially more security holes. And the amount of people that want to run local LLMs is very small. I use local LLMs when I'm on flights, and that is my personal assessment. They are all benchmark-maxed and incapable of reliable tool calling or consistency over meaningfully long conversations.
Hey, I'm Dmitriy from Littlebird. For your use case, would you want the underlying LLM to be local as well, so that your data doesn't get sent to the "big dog" LLM providers? It's an important consideration because it wouldn't be nearly as smart then - though I totally understand if that's the only way it could work for you.
We are SOC2, GDPR, and CCPA compliant btw.
I'm not the OP but I came here to voice the same concern. I would love to use something like this. I also signed up for rewind.ai and Limitless and pre-ordered the pendant. But ultimately I cancelled it out of privacy concerns.
I wonder if it could be local storage and you could provide your own Open Router endpoint? That way it could be a local model or your own deployment of GPT/Claude in Azure/Bedrock/Vertex etc where you can control retention policies etc.
Basically, I want to know that you guys don't have access to view my stuff. I get that that limits your ability to improve the product and support issues, but when I'm sending everything it really starts to matter. Just thought I'd share what held me back from immediately signing up despite really wanting to use a product like this!
Same here. While this looks like it would be beneficial , soon as I saw that all data gets sent to the cloud, It was a blocker.
I have another app that tracks all my usage (time ) at an application. Window level, but I purchased it because it saves locally.
Littlebird is a desktop app that remembers everything you’ve been working on. Meetings, messages, docs, browsing, etc. It helps you stay focused, prioritize, recall, and move projects forward. Unlike any product on the market today, Littlebird uses screenreading to understand all the text on screen, for all applications, without any cumbersome setup. It understands who said what, when, and keeps track of your projects in great detail. It uses that context to build a rich understanding of your life: who matters to you, what you're working on, and what you care about this week and this year. It extends your working memory and your capacity to think and create.
You control what Littlebird sees, what it remembers, and what it forgets. We designed Littlebird to be private, secure, and user-controlled by default.
The screenreading approach is genuinely clever as a distribution strategy — no integrations to maintain, no OAuth flows to break, works on day one with everything. The hard part isn't the tech though, it's the trust problem. Rewind, Limitless, and now this all hit the same wall: the people most likely to benefit from this (busy professionals with complex workflows) are exactly the people most exposed if something goes wrong. Until there's a credible local-first path, the TAM is going to stay small.
If you thought Slack logs were damning in discovery, wait til someone suing or prosecuting you figures out that everything you typed and looked at, etc., is in the cloud
Looks cool! Reminds me of Rewind but better. (edit: for completion)
Agree with this direction. Most tools assume structured inputs, but real workflows are messy and visual. Feels like screen understanding is still very underexplored compared to text.
Screenreading is a smart way to solve the integration problem. Every other tool in this space makes you connect each app one by one and you're always waiting for them to support your workflow. This just watches what you watch. Feels obvious in hindsight - cool stuff
I wish Claude cowork could get better at this. I often end up with Claude performing ad hoc tasks involving multiple windows and it’s so slow. It stops and screenshots and thinks and screenshots to confirm after entering one Google sheet cell of data for example. I’m sure it’ll get better over time.
Hi all, I'm Alex, one of the founders at Littlebird. AMA!
Does your company actually look at resumes? you post in HN but nothing ever goes through. I have a feeling that your recruitment team is not doing their job properly (or being super selective)
I guess it is AMA, anything except about your current hiring pipeline lol
Isn't this a lot like Microsoft's Windows 11 Recall feature that they got a lot of flak for?
tried this last week. typed three words, got back a full breakdown that pulled from three different tools i'd had open. didn't brief it once.
Good tool. Any plans for Windows ? It's my main workstation.
hey! yes, version for Windows is in active development and if everything is fine it will got to beta soon.
Hi folks, Tushar here from the engineering team at Littlebird. AMA!
How are you handling the data extraction? Is it a multimodal VLM (OCR+LLM) or a standard OCR engine feeding a separate LLM? I’ve been hitting a wall trying to understand how this viable. The compute overhead for real-time analysis at scale seems massive without a serious backend. How are you managing the frequency?
Ever consider the enclave route for this kind of work?