DDCL & Automation
One notation connects CRM, data platforms, AI providers, and APIs—so integration intent stays explicit and machine-usable. Then go from how systems should talk to an importable n8n or Logic Apps workflow, without hand-wiring every node.
Domain-Driven Context Language
Format (7 parts)
domain.type.system.provider.protocol.context.action
Example
nova.agent.salesforce.claude.http.territory.analyzeperformance
domain
nova
type
agent
system
salesforce
provider
claude
protocol
http
context
territory
action
analyzeperformance
Parse and validate DDCL strings
Generate DDCL from natural language
Normalize 100+ system aliases (e.g. sf / sfdc → salesforce)
Protocol/system compatibility checks
Visual context relationship graphs
Feedback loops that improve corrections and validation over time
Workflow Automation Generation
Triggers
Agentic patterns (n8n)
Continuous Improvement
Corrections and reviews feed the next design cycle.
Learn from fixes, few-shot style.
Dynamic, runtime-togglable rules.
Measure how much humans change generated docs.
Structured review signals for generation quality.
Ingest your API catalog, cluster related services, and project them into DDCL contexts for architecture and automation.