There has been a lot of talk around building context for AI systems<\/a>. In consumer software, we have seen startups being built around search<\/a>, documents<\/a>, and meetings<\/a>. All of them want to capture context from your digital life, provide connections to other tools, and let you query all that data. Some tools went further. For instance, Rewind<\/a> (which became Limitless and sold to Meta<\/a>) and Microsoft Recall aim to capture everything happening on your screen and help you remember it all.<\/p>\n A new startup called Littlebird<\/a> is trying a similar thing with a slightly different approach. While apps like Rewind store screenshots or some kind of visual data, Littlebird is \u201creading\u201d the screen and storing the context in text format. <\/p>\n The core idea behind the product is that since it is reading your screen all the time, you don\u2019t need to provide additional context for productivity. The startup believes that while a lot of AI tools are trying to distract you, Littlebird can work in the background and can only appear when you want it to.<\/p>\n When you set up Littlebird on your computer, you can customize which apps you want the app to ignore and not capture any context. The startup said that it automatically ignores password managers and sensitive fields in web forms like passwords and credit card details. You can opt to connect other apps like Gmail, Google Calendar, Apple Calendar, and Reminders with the app, as well.<\/p>\n The app lets you ask questions about your data, offering pre-generated prompts to get you started, such as \u201cWhat have I been doing today?\u201d or \u201cWhat kind of emails are important to me?\u201d In a couple of days of usage, I noticed that these prompts became more personalized as time went on.<\/p>\n Littlebird also has an in-built Granola-like notetaker that uses system audio and runs in the background to capture transcription from meetings and create notes and action items based on that. When you open up a meeting in the detailed view, there\u2019s an option called \u201cPrep for meeting\u201d that takes the context of past meetings, emails, and company history into account to give you more details about the meeting. The feature also fetches information from sources like Reddit to inform you what users are thinking about a particular product or a company.<\/p>\n Another tool called Routines offers detailed prompts for Littlebird to run at a repeated interval, such as daily, weekly, or monthly. The company lists some ready-to-use routines like daily briefing, weekly activity summary, and yesterday\u2019s work summary. Users can create their own routines as well with custom instructions.<\/p>\n Littlebird was founded by Alap Shah, Naman Shah, and Alexander Green in 2024. Brothers Alap and Naman founded Sentieo, a platform for institutional investors, which was sold to market intelligence firm AlphaSense. They previously also co-founded a healthy food company called Thistle. Alap was also a co-author of the viral Citrini paper on how AI agents could destroy the economy, which resulted in various tech stocks dipping<\/a>. Green has built various companies in hardware, software, and AI. <\/p>\n \u201cWe got started when Alap posed an interesting problem that AI is going to be about your [users\u2019] data. Models don\u2019t know anything about you, and that limits their utility. We were thinking about various UI and OS paradigms that were likely to be ripe for disruption with AI and that kicked off Littlebird as a project,\u201d Green told TechCrunch over a call. <\/p>\n Green noted that while Rewind was close to what Littlebird is trying to do, it relied on screenshots and didn\u2019t have a great search experience. He said that the startup is just getting started and there are many more problems to solve, including making large language models (LLMs) understand different kinds of context about users.<\/p>\n With Littlebird, users can remove their data at any time, and their data is stored in the cloud with encryption. Green said that the rationale behind storing the data in the cloud was to run powerful models for different AI workflows, which is not possible locally.<\/p>\n \u201cWe don\u2019t store any visual information. We only store text, which makes the data a lot lighter-weight. I think that was probably another reason that Recall and Rewind struggled, which is that taking a screenshot is a lot more data hungry. I also think it\u2019s more invasive,\u201d he said. <\/p>\n Littlebird is free to download and use, but to get more usage limits and access to features like image generation, users can pay for plans starting from $20 per month.<\/p>\n The startup has raised $11 million in funding led by Lotus Studio, with participation from Lenny Rachitsky, Scott Belsky, Gokul Rajaram, Justin Rosenstein, Shawn Wang, and Russ Heddleston.<\/p>\n Several of these investors are regular users of the product. Rajaram, who has worked at Google and Facebook on ad products, said that the product removes the friction of remembering, retrieving, and re-explaining your own work. DocSend co-founder and CEO Heddleston said that he rewrote the company\u2019s marketing site using the tool, using context from meetings, email, Notion, and more.<\/p>\n Rachitsky, who runs his own newsletter and podcast, said that AI is as good as the context it has, and it misses so much about your day. He said he asks the tool about improving his productivity workflows and being happier. He said that for long-term success, the product will need to find a killer use case. <\/p>\n \u201cI think it\u2019s all about finding that killer must-have use case. That\u2019s all that matters to this product\u2019s success right now. I know a lot of people already have found that for themselves, and the team is leaning into these experiences as they see these use cases emerge,\u201d he noted.<\/p>\n \u201cI\u2019ve had a lot of AI product builders on the podcast, and the most consistent theme is that you don\u2019t actually know how people will use your product until you put it out. The strategy is to put out early stuff, see how people use it, and double down on those use cases versus waiting for something totally figured out.\u201d<\/p>\n<\/div>\n![\"\"](\"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/03\/Light-Meeting-Note.jpeg?w=680\")
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