Linni
A personal operating system for work, memory, planning, and AI.
Linni is Venn Labs' first app: an offline-first, AI-assisted productivity system built on the Venn Labs architecture—a relationship graph and planning and attention metadata—so the assistant is fed computed context, not a generic thread.
Product promise
Organize your world. Plan your work. Ask with the right context.
Linni is a strong productivity tool on its own. When you use the assistant, it benefits from the same structure, decorators, and orchestration the company is building—pins, flags, next actions, details, and routing as part of the product, not a bolt-on.
Product Philosophy
The system comes first. The intelligence builds on it.
Capture should be fast, but not structureless.
Planning should emerge from relationships between work, time, and context.
AI should understand and extend the user's system instead of replacing it.
Context should be built deliberately—intent, data, and policy—not stuffed into a single prompt.
Personal data should be local-first, synchronized, and protected.
The product should remain useful even when AI is not used.
Linni Lingo
A personal productivity methodology, built for daily life.
Linni uses a personal productivity methodology on top of the Venn Labs architecture, with friendlier terms that fit daily planning, memory, and follow-through. The structure is the same; the language is tuned for personal work, with Spaces as the highest level in the organizing hierarchy.
The underlying architecture gives Linni a precise framework underneath the product, while Linni Lingo keeps the interface grounded in the way people already think about their lives and work.
A Space is the highest level of organization, such as work, home, health, or a creative project.
Goals, Contexts, and Topics form the organizing middle layer for planning a real week.
Actions, Events, and Notes describe what you do, what happens, and what you want to remember.
Flags, Stars, Pins, Details, and Categories turn metadata into simple planning cues.
Product pillars
Structured capture
Capture tasks, notes, events, goals, ideas, and conversations without losing their meaning.
Connected planning
Link work across goals, contexts, topics, and spaces so planning reflects real life.
Contextual, orchestrated AI
Intent, assembled context, and safe proposals—not only the last message you typed. Model routing without treating one model as memory.
Offline-first reliability
Keep working locally, then sync across devices when the network is available.
Layered privacy
Use everyday system encryption by default and a private vault for sensitive work and attachments.
Product architecture
One connected system, not a bundle of separate tools.
The same data powers lists, calendar, log, and AI. That is the point: a single operable model your assistant can be grounded in, with a control loop for how much context to send and when to change data.
Calendar home base with day and month views
To Plan for unscheduled, overdue, or unconnected work
Spaces as the highest level in the organizing hierarchy
Goals, Contexts, and Topics as the organizing middle layer
Actions, Events, and Notes connected through relationships
System Log and search across history, interactions, and records
Device calendar import, recurring work, reminders, and bulk operations
AI that uses structure
Contextual, controlled, and connected to real work.
Linni can supply the assistant with profile and Space context, the active Set, connected Elements, recency, today's schedule, overdue work, and conversation history—plus planning signals and policy from the graph and decorators.
For data changes, Linni can show a human-readable proposal before applying it, so the user stays in control. That is part of the same orchestration story as intent and routing, not a separate add-on. Persistent memory stays in the structured app data, not inside one model.
Built for daily reliability.
Linni writes locally first, synchronizes in the background, supports local reminders, and includes health visibility for sync and diagnostics. Data is encrypted, and sensitive Actions, Events, Notes, and attachments can use a higher-security vault model, with clear boundaries for what enters AI context.
Learn about trust