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.
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?
hi, while vision is going to be a part, it's hard to scale both on server and the client(it's resource intensive and the battery will drain faster on client). we hook deeper into the OS layer with accessibility, Apple Script and other ways to get raw text. This also lets us create a privacy friendly app with granular data controls for the user.
> compute overhead for real-time analysis at scale seems massive without a serious backend.
you're still right about this part though, and we do have a serious backend.
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
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.
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
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.
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.
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[ 3.6 ms ] story [ 36.0 ms ] threadYou control what Littlebird sees, what it remembers, and what it forgets. We designed Littlebird to be private, secure, and user-controlled by default.
> compute overhead for real-time analysis at scale seems massive without a serious backend. you're still right about this part though, and we do have a serious backend.
Good tool. Any plans for Windows ? It's my main workstation.