Capture useful context.
Supported workflows can capture goals, decisions, project state, and next actions without turning memory into another task.
Your agents from different vendors and different models share one centralized memory – encrypted end-to-end, private by design, and built to just work. What one agent learns, every agent remembers.
Two-minute install – one command in your terminal, or a macOS installer.
Gitmas captures useful context from supported workflows and makes it available across projects, sessions, checkpoints, and time periods. Important decisions can also be saved explicitly when needed.
Supported workflows can capture goals, decisions, project state, and next actions without turning memory into another task.
Claude Code, Codex, Pi, Hermes, Gemini, scripts, and future clients can request relevant memory from any point in the work.
Autosave scans your agent transcripts every minute and archives them encrypted. Closing a terminal is never the moment that decides whether your work was saved.
Store a rule once – every agent, from every vendor, on every device gets it injected at session start. Hard rules stop depending on whether an agent remembers to ask.
Browse every session in the dashboard, open full transcripts with syntax-highlighted code and in-text search, and jump from a checkpoint straight to the moment it describes.
Storing, syncing and archiving happen outside the model – no tokens spent. Recall is on-demand: one short memory hit typically replaces thousands of tokens of re-reading and re-explaining. Shared memory doesn’t inflate your AI bill – it shrinks it.
Launch pricing for builders who already use AI agents on real projects.
Agents can retrieve the project goal, last decision, older checkpoint, or session trail when the work needs it.
Each connected agent can use relevant context from previous sessions, tools, projects, and time periods.
Encrypted full-session saves keep the trail available for backup, review, and recovery.
Your memory and session archives stay yours. They are not sold or used to train models.