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Saphira Linux

AI

Saphira Linux aiDragon

A practical Saphira workspace for AI agents: your code, services, databases and tools stay under your control, while the model can run wherever it works best.

In testing, functionality present — helpers missing
Saphira Linux aiDragon, the AI agent workspace mascot

Memory makes an agent a better collaborator

Context matters. An agent that understands a project, its architecture, previous decisions and why those decisions were made is dramatically more useful than one repeatedly dropped into an unknown directory and asked to guess. Persistent memory lets useful project knowledge survive between sessions instead of being rediscovered each time.

The MCP memory-server approach is a simple place to begin. We also use a lightweight SQLite-backed memory system ourselves. A combined MariaDB-backed memory implementation is in development, but is not yet a finished public Saphira feature.

GoodThe model may be remote. The memory, tools, source code, infrastructure and decisions can remain yours.