Screenpipe
Screenpipe captures a user's screen, audio, and app activity locally, then lets AI agents search that history to understand work patterns, draft summaries, and identify automation opportunities. The tool maps recurring workflows across applications, such as invoice processing, and suggests specific automations like drafting tracker entries. It integrates with AI harnesses including Zapier, n8n, Claude Code, and Codex, with raw history staying on-device by default.
- Enterprise Software
- Artificial Intelligence
- AI Agents
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Knowledge workers lose significant time searching for past context across multiple apps and windows, and repetitive manual workflows like invoice processing or follow-up drafting are hard to automate without a complete record of how work actually happens. Existing productivity tools lack a comprehensive, searchable history of a user's on-screen and audio activity that AI agents can act upon.
Solution
Screenpipe keeps a local-first record of screen, audio, and app activity, then lets users query that history through natural language. AI agents can search the captured data to understand a user's work patterns, draft summaries and follow-ups, and map multi-step workflows from observed behavior. The tool identifies repetitive steps and suggests automations, such as generating tracker entries from invoice processing. Raw history stays on the device by default, and users control what is captured and what is shared with cloud AI providers.
Target Audience
Individual knowledge workers, teams, and enterprise customers who want to reduce manual documentation and find automation opportunities in their existing daily computer use. Enterprise operations teams, automation teams, and people building AI agents who need to understand how work happens across applications.
Features
- Local-first capture of screen, audio, and app history with on-device storage by default
- Natural-language AI search across captured work history for answering questions like "Map how I processed invoices this week"
- Workflow mapping that identifies recurring steps across apps and suggests specific automations (e.g., drafting tracker entries and flagging mismatches)
- AI interviews that capture decisions, exceptions, and checks the recording cannot explain
- Configurable capture exclusions, pause controls, and retention policies for privacy-sensitive content
- Integration with multiple AI harnesses including Zapier, n8n, Claude Code, and Codex, plus exports, APIs, and MCP support
- Optional enterprise model training on company workflows using approved data