Organizational modeling
Connect organizational sources and model entities, concepts, relationships, processes and terminology.
Technology
Atlas is a managed organizational context layer for AI applications. Its architecture connects organizational sources, resolves entities and relationships, respects permissions, preserves evidence and delivers relevant context.
System architecture
Ingestion + processing
Organizational modeling + entity resolution
Hybrid retrieval
Graph-based context
Authorization + provenance
Context assembly + delivery
Durable organizational memory
Connect organizational sources and model entities, concepts, relationships, processes and terminology.
Assemble the context relevant to a task, instead of returning isolated documents.
Combine semantic retrieval and graph relationships to follow relevant context across organizational sources.
Keep the source and basis of context visible so applications can work with evidence, not opaque text.
Treat authority and access boundaries as part of context retrieval and delivery.
Carry organizational knowledge and history forward for use across applications and teams.
Deliver assembled organizational context to the agent or application that requests it.
Account for changes in source systems and organizational information over time.
Make context quality and evidence inspectable as part of evaluating AI applications.
Why a graph?
Important questions depend on relationships: ownership, dependencies, affected customers, supporting evidence, changes over time and downstream consequences. A graph provides the relationship layer Atlas uses to assemble that context.
About Atlas
Atlas is in active development and early access. AhiaIntel is building a managed organizational context layer for teams creating AI applications.
Explore Atlas