screenpipe vs siift: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of screenpipe and siift — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

screenpipe

Screenpipe

Freemium

Local-first app that continuously records your screen and audio, then serves that computer history to AI agents via API and MCP.

Continuous Local Capture: Records screen and audio 24/7 into a local SQLite database, capturing the full accessibility tree with OCR fallback, transcripts, speakers, keystrokes and app switches.
Natural-Language AI Search: Ask what you saw, said or heard in plain language and jump back to the original on-screen evidence in seconds instead of retracing tabs.
Local REST API and MCP Server: Expose your history at localhost:3030 or add it to Claude, Cursor and other clients with one MCP command so any agent can query it.
Pipes and Automations: Build agents and scheduled tasks that react to what you actually do, such as updating Linear whenever you work on a given task or drafting a daily summary.
Automatic Meeting Notes: Transcribes calls with speaker attribution and produces notes and follow-ups without a separate meeting bot joining the call.
Privacy Filters and Encryption: Filter by window, app or Chrome extension, redact passwords and PII with a dedicated model, encrypt at rest, and run entirely offline.
50+ App Integrations: Push captured context into Notion, Gmail, Zoom, Slack and dozens of other tools already in your workflow.
Source-Available and Portable: Inspect, modify and audit the source, and keep your history in your own database rather than locked to one model vendor.

Recovering Lost Context: Find the document, message or screen you saw days ago by searching what was actually on your display rather than remembering where it lived.
Meeting Follow-Through: Automatically transcribe and summarize calls, then surface the commitments and follow-ups you would otherwise forget.
Grounding Coding Agents: Give Claude, Codex or a custom agent real evidence of your session so it works from what happened instead of guesswork.
Personal Daily Summaries: Generate an end-of-day recap and calendar blocks for critical tasks from your real activity, including into tools like Obsidian.
Project Audit Trails: Record the flow of information and instructions across multiple projects and file it per project for later review.
Discovering Automation Opportunities: Let the enterprise tier analyze repeated manual work to find savings and candidates for automation.

Freemium

An agentic AI operating system that helps founders map, validate and execute business strategy on one intelligent canvas.

Intelligent Business Canvas: A visual workspace that maps ideas, assumptions, actions and results into decision-ready filters so the whole business can be seen at once.
Living Memory System: A scalable agentic memory that learns as the business evolves and keeps context aligned across tools, data and teammates.
AI-Scored Validation: Automated, continuous research that grades assumptions into evidence so founders know what is validated and what is still risky.
Five-Stage Execution Loop: Guided progression through Ideate, Validate, Build, Go To Market and Scale, each with its own AI-driven workflow.
Safe Stack Automations: Human-in-the-loop actions across 80+ popular applications so approved work executes without leaving the canvas.
Shareable Workspaces: Collaborative views that let teammates, advisors and other stakeholders work from the same strategy context.
Proactive Next-Step Guidance: Personalized, iterative advice that surfaces the highest-leverage action rather than a generic checklist.
Credit-Based AI Usage: Monthly request credits scaled by plan and weighted by task complexity, with unlimited projects even on the free tier.

Idea Validation: De-risking a new business concept by turning founder assumptions into automatically researched, scored evidence before building.
Strategy Mapping: Turning a cloud of unstructured ideas into a visual mind-map that exposes blindspots across the business model.
Go-To-Market Planning: Iterating on sales and marketing with an AI-native loop that tests which channels actually produce revenue.
Product Prioritization: Helping product leaders decide what to build next based on verified market opportunities rather than intuition.
Scaling Diagnostics: Systematizing an existing business to surface its current growth constraints and reverse-engineer fixes.
Advisor Collaboration: Sharing a single live strategy workspace with co-founders, advisors and investors instead of static decks.