Littlebird raises $11M for its AI-assisted ‘recall’ tool that reads your computer screen

Startups are increasingly focusing on building context for AI systems. In consumer software, companies are developing tools around search, documents, and meetings. These platforms aim to capture data from users’ digital activity and make it searchable.

At the same time, some products go further. Tools like Rewind AI and Microsoft Recall attempt to record everything on a user’s screen to improve recall.

However, approaches to capturing this data continue to evolve.

Littlebird takes a text-first approach

A new startup, Littlebird, is building a similar product with a different method. Instead of storing screenshots or visual data, the platform reads screen activity and converts it into text.

This approach reduces data size and changes how information is stored. As a result, users can search and interact with their activity without relying on images.

The company states that continuous screen reading removes the need for users to manually provide context. Instead, the system runs in the background and becomes visible only when needed.

Custom controls and integrations

Users can control what data Littlebird captures. During setup, they can exclude specific apps from tracking. The system also avoids sensitive inputs such as passwords and credit card fields.

In addition, users can connect external tools. These include Gmail, Google Calendar, Apple Calendar, and Reminders. This expands the range of context the system can access.

Query-based insights and personalization

The platform allows users to ask questions about their activity. It also provides pre-set prompts such as “What have I been doing today?” or “What kind of emails are important to me?”

Over time, these prompts become more personalized. This reflects changes in user behavior and usage patterns.

Meeting notes and contextual preparation

Littlebird includes a built-in note-taking feature. It uses system audio to transcribe meetings and generate summaries and action points.

Moreover, it offers a “Prep for meeting” option. This feature gathers context from past meetings, emails, and company data. It also pulls insights from platforms like Reddit to provide broader context.

Automated routines for recurring tasks

The platform also supports automation through “Routines.” These are scheduled prompts that run daily, weekly, or monthly.

Users can choose from preset options such as daily briefings or weekly summaries. Alternatively, they can create custom routines with specific instructions.

Founders and early development

Littlebird was founded in 2024 by Alap Shah, Naman Shah, and Alexander Green.

Alap and Naman previously built Sentieo, which was later acquired by AlphaSense. They also co-founded a health-focused company, Thistle.

Green has experience across hardware, software, and AI ventures.

“We got started when Alap posed an interesting problem that AI is going to be about your [users’] data. Models don’t 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,” Green told TechCrunch over a call.

Challenges in building contextual AI

Green noted that existing tools like Rewind rely heavily on screenshots. According to him, this limits search quality and increases data load.

He added that the company is still early in development. Several challenges remain, especially in helping large language models understand different types of user context.

Privacy and data storage decisions

Littlebird allows users to delete their data at any time. The company stores information in the cloud using encryption.

Green explained that cloud storage enables the use of more powerful AI models. Running such models locally would be difficult.

“We don’t 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’s more invasive,” he said.

Pricing and monetization

The product is free to use with limited access. Paid plans start at $20 per month and include additional features such as image generation.

Funding and investor perspective

Littlebird has raised $11 million in funding. The round was led by Lotus Studio, with participation from investors including Lenny Rachitsky, Scott Belsky, Gokul Rajaram, Justin Rosenstein, Shawn Wang, and Russ Heddleston.

Several investors are also active users of the product. Rajaram said the tool reduces friction in recalling and explaining work. Heddleston noted that he used it to rewrite his company’s marketing site.

Rachitsky highlighted that AI performance depends heavily on context. He added that long-term success will depend on identifying a strong use case.

“I think it’s all about finding that killer must-have use case. That’s all that matters to this product’s 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,” he noted.

“I’ve had a lot of AI product builders on the podcast, and the most consistent theme is that you don’t 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.”