Littlebird has launched a new AI-powered productivity tool designed to capture and structure user context by reading on-screen activity in real time. Unlike competitors such as Rewind AI and Microsoft Recall, which rely on screenshots or visual recordings, Littlebird converts screen content into text-based data for analysis and retrieval.
The system continuously processes user activity across applications while allowing customization to exclude sensitive tools such as password managers or financial inputs. It can also integrate with services including Gmail, Google Calendar, Apple Calendar, and Reminders to expand its contextual dataset.
Littlebird enables users to query their activity using natural language prompts, which evolve over time based on usage patterns. The platform also includes a built-in meeting assistant that transcribes audio, generates summaries, and prepares contextual briefings by combining data from past interactions, emails, and external sources.
A separate feature, Routines, allows users to automate recurring insights such as daily summaries or weekly reports. These workflows reflect a broader trend in AI toward passive, always-on systems that operate in the background rather than requiring active input.
The startup was founded in 2024 by Alap Shah, Naman Shah, and Alexander Green. It has raised $11 million in funding led by Lotus Studio, with participation from industry operators and angel investors.
Littlebird stores encrypted user data in the cloud to support large-scale AI processing. The company argues that its text-first approach reduces storage demands and improves searchability while addressing privacy concerns tied to image-based capture systems.
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