A model is not your organisation's memory.
Language models bring general capability, but they do not automatically understand your decisions, clients, operating boundaries or the lessons behind your processes. Prompt history is temporary, and a document index rarely captures experience.
Macrosona gives agents a durable source of organisation-specific context that can be reused across tools and sessions.
Ground agent reasoning in evidence and provenance.
Retrieval is more useful when an agent can distinguish an exact quote from a reported fact or a developed lesson. Macrosona keeps those memory types distinct and returns lineage so people can inspect why a result was surfaced.
- Persistent memory across approved agent conversations.
- Context-aware retrieval scoped to the relevant client or project.
- Source citations and surrounding evidence for inspection.
- Portable connections for compatible AI tools and agents.
Memory that respects organisational boundaries.
Useful agent memory cannot be one unrestricted pool. Macrosona uses workspace, source and contextual boundaries so retrieval can remain relevant without collapsing separate clients, teams or projects together.