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Understanding these building blocks will help you navigate every other part of the documentation.

The core loop

Causeloop is organized around a single closed loop that turns raw failures into verified fixes.
1

Issue

A discrete failure event — an incident, a defect, a failed check. Issues arrive automatically from connected sources or are created directly via the API or UI.
2

Pattern

Causeloop groups related issues by shared root-cause fingerprint. A pattern surfaces the recurring failure behind a set of issues rather than treating each one as isolated.
3

Prediction

From each pattern’s frequency and signal history, Causeloop predicts where and when the failure is likely to recur — giving you a window to act before it does.
4

Recommendation

Causeloop proposes a concrete remediation, tracks whether the pattern’s issues stop appearing, and marks the recommendation implemented when the fix holds.
The loop closes when a recommendation is verified. If new issues matching the pattern appear after a fix, the loop reopens automatically.

Tenancy model

Organization

The top-level account — one per client. Carries the plan, seat count, and billing identity. Status: active, suspended, or cancelled.

Workspace

The data boundary owned by an organization. All issues, patterns, connectors, and settings live inside a workspace. One organization typically has one workspace, but the model supports more.

Membership

The link between a user and a workspace. Carries the role that governs what the user can do inside that workspace.

Organization

An organization is the client entity. It owns one or more workspaces and controls plan-level constraints:
FieldNotes
slugURL-safe unique identifier (e.g. acme)
planfree / starter / growth / enterprise
seats_totalMaximum active memberships
statusactive / suspended / cancelled

Workspace

A workspace is the operational data boundary. Every API call resolves to a single workspace; Row-Level Security (RLS) enforces that no query can read another tenant’s data.
FieldNotes
slugUnique within the organization
timezoneDefault display timezone for all reports
sso_enforcedWhen true, password login is blocked for the workspace
Each workspace has a companion workspace_settings record controlling AI confidence thresholds, retention policies, and alert sensitivity, and an onboarding_state record that drives the setup wizard.

User

A user is a global identity (unique by email). The external_id field stores the Clerk subject ID when the user authenticates through Clerk or another IdP.

Membership

A membership joins a user to a workspace with a role. Roles are cumulative — each role includes all permissions of the roles below it:
RoleCan do
viewerRead issues, patterns, predictions, recommendations, and reports
analystEverything above, plus create/update issues, link patterns, trigger analysis, create connectors
adminEverything above, plus invite members, manage settings, create alert rules, export data
ownerEverything above, plus manage organization settings, billing, and SSO
A user can belong to multiple workspaces with different roles in each.

Product entities

Issue

An issue is a single failure event ingested from a connected source or created manually.
FieldValues
severityp1 (critical) · p2 · p3 · p4
statusopen · in_loop · mitigating · resolved · closed
sourceThe connector type that originated the issue (e.g. pagerduty, jira, github)
risk_score0–100 composite risk signal
An issue moves through statuses as it is investigated and linked to a pattern. Issues with status in_loop are actively being analyzed as part of a pattern.

Pattern

A pattern groups issues that share the same underlying root cause. Causeloop detects patterns automatically by clustering issues on their fingerprint (signal dimensions such as service, error type, time-of-day, and affected team).
FieldValues
statusemerging · active · resolved
risk_score0–100 aggregate signal
confidence0.0–1.0 model confidence that the grouping is accurate
fingerprintKey–value map of the shared signal dimensions
A pattern transitions to resolved when a closure note is recorded and its open member issues stop recurring within the configured proof window.

Cluster

A cluster is a higher-order grouping of patterns that share structural relationships (common services, overlapping time windows, or shared contributing factors). Clusters appear in the pattern graph view and help you see which patterns belong to the same systemic problem. Clusters are computed asynchronously. You can trigger a recompute via POST /clusters/recompute.

Prediction

A prediction is a forward-looking risk signal derived from a pattern’s recurrence history.
FieldNotes
probability0.0–1.0 likelihood the pattern recurs within window_days
window_daysForecast horizon in days
impactcritical / high / medium / low
likely_triggerAI-generated description of what will likely cause the next recurrence
The prediction model is evaluated continuously. You can record feedback (hit / miss / prevented) on each prediction to improve accuracy over time.

Recommendation

A recommendation is a ranked, actionable remediation tied to one or more patterns.
FieldValues
statuspending · in_progress · implemented · dismissed
effortlow / medium / high
impacthigh / medium / quick_win
rankPriority order within the workspace (1 = highest)
expected_loops_preventedModel estimate of recurrences eliminated if this fix holds
Recommendations can be pushed directly to your issue tracker (Jira, Linear, GitHub, ServiceNow) via POST /recommendations/{id}/push.

Integration entities

Connector

A connector is a configured integration with an external tool. Connectors pull issue data into Causeloop on a schedule or respond to inbound webhooks. Causeloop supports 70+ connector types organized by category:
CategoryExamples
Cloud & MonitoringDatadog, Dynatrace, New Relic, AWS CloudWatch
Productivity & IncidentPagerDuty, Jira, GitHub, Linear, Opsgenie
CRM & SupportSalesforce, Zendesk, HubSpot
DataPostgreSQL, Snowflake, BigQuery
SecurityOkta, CrowdStrike, Splunk
Each connector has a status (active / paused / error), a configurable poll_interval_seconds, and a sync run history.

Plan and seat concepts

Plan

A plan is the subscription tier of an organization: free, starter, growth, or enterprise. The plan controls feature flags, rate limits, and which connectors are available.

Seat

A seat is one active membership slot. The organization’s seats_total cap limits how many concurrent active memberships a workspace can hold. Suspending a membership frees the seat without deleting the user’s data.

Quick reference

TermOne-line definition
OrganizationTop-level client account
WorkspaceData boundary; all product data lives here
UserGlobal identity (unique email)
MembershipUser ↔ Workspace link with a role
IssueA single failure event
PatternA cluster of related issues sharing a root cause
ClusterA grouping of related patterns
PredictionA forward-looking recurrence risk signal
RecommendationA ranked, trackable fix for a pattern
ConnectorA configured integration that feeds issues in
PlanSubscription tier controlling features and limits
SeatOne active membership slot against the org’s cap

Quickstart

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Architecture

Understand how the platform layers fit together.