Runtime path

Glue Visual ETL
  └─ SQL / JDBC → connector + translator
                         └─ Cypher / Bolt → Neo4j

• Driver: org.neo4j.jdbc.Neo4jDriver
• Enable: enableSQLTranslation=true

The mapping in practice

Movie                     → (:Movie)
title                     → .title
Person_ACTED_IN_Movie     →
(:Person)-[:ACTED_IN]->(:Movie)

SELECT m.title FROM Movie m

MATCH (m:Movie)
RETURN m.title

• Private meaning: Each agent carries its own interpretation of the business.
• Private routing: Each agent decides which source or tool is authoritative.
• Private policy: Rules are repeated across prompts and integrations.
• Silent drift: Every answer can sound reasonable while the enterprise loses a consistent view.

Same term, different meanings

"active customer"

Agent A → signed in within 30 days
Agent B → current paid contract
Agent C → open account balance

• One shared layer: Maintain enterprise knowledge once and reuse it across consumers.
• Connected context: Link concepts to data, policies, owners, and processes.
• Current by design: Query the layer while work is happening instead of copying it into prompts.
• Lighter agents: Keep task logic in the agent and enterprise meaning in the shared layer.

• Shared: Reuse business meaning and operating knowledge across consumers.
• Governed: Keep sources, policies, ownership, and accountability explicit.
• Queryable: Retrieve the exact context required for each request.
• Actionable: Map intent to authoritative sources, permitted tools, and executable queries.

• Knowledge Layer ontology: Defines what things mean, how they connect, where their data lives, what rules apply, and who is accountable.
• Enterprise data: Supplies authoritative facts about what is true now.
• Memory: Captures previous actions, decisions, outcomes, and reasoning.

Narrow: Conceptual Map

• Defines what business concepts mean and how they relate.
• Includes concepts such as Customer, Purchase, and Product.
• Does not refer to Salesforce, tables, APIs, or other physical systems.

Broad: Knowledge Layer ontology

• Connects five sub-ontologies: domain, technical, process, policy, and organization.
• Includes descriptions of technical assets and mappings from business concepts to them.
• Does not require the actual enterprise records to be stored in the ontology.

• Domain: Business concepts and relationships.
• Technical: Descriptions of systems, sources, and data assets, plus mappings from business concepts to those assets.
• Process: Tasks, decisions, workflows, and actions.
• Policy: Access rules, conditions, constraints, and permitted actions.
• Organization: Roles, ownership, responsibilities, and accountability.

• Domain ontology: Provides concepts such as “Customer,” “Purchase,” and “Product.”
• Technical ontology: Describes systems and assets such as Salesforce and its Opportunity table.
• Semantic map: Connects the two: PURCHASE → Salesforce.Opportunity.
• Enterprise data: Supplies the actual opportunity records from Salesforce.

• Interpret intent: Resolve the business meaning of the request.
• Assemble context: Select authoritative sources and relationships.
• Route queries and tools: Translate concepts into calls against AWS systems.
• Enforce policy: Apply access and action rules during resolution.
• Explain and learn: Return evidence and lineage, then retain useful outcomes.

• Meaning: Concepts resolved for the request.
• Sources: Authoritative systems, queries, and lineage.
• Policy: Access and action checks applied.
• Evidence: Facts supporting the current result.
• Precedent: Prior decisions, only when they influenced the result.
• Outcome: The result or action, observed outcome, and feedback.

• Long-term knowledge: Entities, relationships, business meaning, policies, and authoritative facts.
• Short-term state: Conversation, user intent, task, workflow state, and tool observations.
• Reasoning memory: Decisions linked to their situation, rationale, actions, outcomes, and precedents.