# Enterprise Context Sharing

Large enterprises accumulate organizational knowledge in silos. The HR
department maintains org charts in Workday. Engineering tracks service
dependencies in a custom Memgraph instance. Product manages feature hierarchies
in Jira. Sales stores account relationships in Salesforce. Each team chose the
right tool for their job, but now no one has a unified view of how these
domains connect.

MemGQL solves this by providing a federated knowledge graph that overlays
canonical context—org charts, product hierarchies, ontologies—onto each team's
existing data stores. Departments keep their preferred tools and schemas while
gaining a unified graph view that crosses organizational boundaries.

## The Problem

Enterprise context sharing faces four fundamental challenges:

1. **Tool Diversity**: Each department optimized for their specific needs. HR
needs hierarchical reporting; Engineering needs graph relationships; Sales
needs relational CRM. Forcing everyone into one database creates friction and
adoption resistance.

2. **Schema Drift**: Even when teams use the same database type, their schemas
diverge. One team's `Employee` table has different columns than another's.
Maintaining a central canonical schema requires constant synchronization that
never quite works.

3. **Ownership Boundaries**: Data ownership is organizational. The HR system is
owned by HR; Engineering's service graph is owned by Platform Engineering.
Centralizing this data requires political capital and creates single points of
failure.

4. **Secure Data Access**: Each departmental system enforces its own security
policies, authentication mechanisms, and authorization rules. Creating a unified
view risks bypassing these controls or creating inconsistent security
postures. Sensitive data—employee salaries, unreleased product features,
customer contracts—must remain protected while still enabling authorized
cross-domain queries.

## The Solution

MemGQL provides a virtualization layer that maps each team's native schema into
a shared enterprise ontology. The underlying data stays in place; only the
graph view is unified.