Ontology
The ontology is your organization's knowledge graph: a continuously updated map of every entity in your infrastructure and the relationships connecting them.
What the ontology contains
SixDegree discovers entities from connected integrations and stores them as typed nodes in the graph. Relationships between those nodes are inferred automatically from the data each integration provides.
| Element | Examples |
|---|---|
| Entities | Accounts, opportunities, subscriptions, tickets, incidents, vendors, contracts, people, services |
| Relationships | OWNS, RENEWS, ESCALATED_TO, BELONGS_TO, DEPENDS_ON |
| Attributes | Last updated, owner, status, tags, and integration-specific metadata |
As your business changes, the graph updates automatically. New opportunities, ticket escalations, and renewals reflect immediately. No manual documentation step required.
LLMs only know what they were trained on. To reason about your specific infrastructure without hallucinating, an LLM needs accurate, real-time context about your systems. The ontology provides exactly that.
The object-oriented model
Entities in the ontology work like objects in object-oriented programming. Tools are the methods that operate on them: retrieving ephemeral data or taking actions.
SalesforceAccount.getOpenOpportunities() // real-time data, not stored in graph
ZendeskTicket.escalate(reason) // action executed via molecule
PagerDutyService.getIncidents() // live fetch from PagerDuty API
GitHubRepository.createIssue(title) // write action
Only long-living resources are stored in the graph. Ephemeral data (open opportunities, active incidents, recent tickets) is fetched on demand through tools at query time. This keeps the graph lean while giving the AI a complete, grounded picture when it reasons.
This separation matters for performance. The graph answers "what exists and how does it connect" instantly. Tools answer "what is happening right now" by calling the upstream API.
Why the ontology matters
Traditional documentation goes stale immediately. Wikis fall behind. Tribal knowledge lives in people's heads and leaves with them. The ontology solves this by treating discovery as infrastructure, not documentation.
| Role | Benefit |
|---|---|
| Revenue ops | See every touchpoint behind an account before a renewal: open opportunities, support escalations, and product usage in one view. |
| Support | Trace an SLA breach to the incident behind it and the revenue it puts at risk, without hopping between tools. |
| Operations | Know which vendors and contracts back each team, and where spend no longer maps to usage. |
| Engineering | See what depends on the code you're changing before you ship, and who owns it. |
Exploring the graph
The ontology appears as an interactive graph in your dashboard. Nodes represent entities; edges show relationships. Node color indicates entity type.
Screenshot needed: Full-page graph view: colored nodes for different entity types (Salesforce accounts blue, Zendesk tickets green, PagerDuty incidents orange), edges labeled with relationships, search and filter chips at the top.
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Click any node to open its detail panel: full attributes, grouped relationships, and a shortcut to open it in the AI chat.
Screenshot needed: Entity detail side-panel that slides in when you click a node: entity name, type, attributes, relationships grouped by type, and a "Show in chat" button.
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Patterns the graph reveals
- Accounts with an open escalation and a renewal due soon
- Hidden dependencies between revenue, support, and the systems behind them
- Vendors and contracts no team used this quarter
- Ownership gaps where no one is accountable for an account or service
Common uses
Account context
Ask the AI "show every touchpoint for this account: tickets, calls, and product usage" to get the full picture before a renewal call, without stitching together five tabs.
Escalation impact
Trace an SLA breach to the incident behind it and the revenue it puts at risk. The graph answers blast-radius questions in seconds, across support and revenue at once.
Spend review
Ask "which vendors are we paying for that no team used this quarter" to surface contracts and spend that no longer map to usage, in one traversal.
Finding owners
Every entity shows current ownership and accountable contacts, whether that's the account owner, the on-call responder, or the team behind a service.
Building a complete picture
The ontology grows as you connect more integrations. Each molecule adds a new layer:
Salesforce → accounts, opportunities, contacts
Zendesk → tickets, organizations, agents
Stripe → subscriptions, invoices, customers
NetSuite → vendors, contracts, spend
PagerDuty → services, on-call schedules, escalation policies
GitHub → repositories, pull requests, users, teams
The ontology reflects only what your connected molecules can discover. An entity that exists only in a disconnected system will not appear in the graph and will not be visible to the AI.
Next steps
- Entities and Relationships: the building blocks of the graph
- Querying the graph: how questions become fast, exact answers
- Tools: how the AI retrieves live data and takes actions
- Exploring the Ontology: navigate the graph in your dashboard
- Molecules: add integrations to expand discovery coverage