Connect your entire stack
CauseFlow integrates with your existing tools — monitoring, code, databases, and customer support. Each one mapped to a specialized AI agent.
Integration Catalog
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
AWS CloudWatch
Analyzes error logs, metrics, and alarms from AWS infrastructure in real time.
🔗log_analyst, metric_analyst
Datadog
Ingests metrics, logs, and distributed traces to identify performance anomalies.
🔗log_analyst, metric_analyst
Sentry
Captures real-time errors, exceptions, and stack traces for root cause analysis.
🔗ingestion
PagerDuty
Receives alert payloads and on-call context to trigger automated investigations.
🔗ingestion
Grafana
Reads dashboard panels and alert states to correlate metrics with incidents.
🔗metric_analyst
New Relic
Analyzes APM traces, error rates, and infrastructure metrics.
🔗log_analyst, metric_analyst
Opsgenie
Ingests alert payloads and on-call schedule data to start investigations.
🔗ingestion
Splunk
Queries log indexes and saved searches to surface relevant error patterns.
🔗log_analyst
Slack
Receives incident reports from engineering and support. Responds directly in incident channels.
🔗notification
Microsoft Teams
Accepts investigations triggered from Teams channels and posts results as replies.
🔗notification
Discord
Delivers investigation summaries and root cause findings to Discord channels.
🔗notification
GitHub
Analyzes commits, PRs, and recent releases. Generates and opens fix PRs.
🔗code_analyzer, code_fixer
GitLab
Reads merge requests, pipelines, and commit history for change correlation.
🔗code_analyzer, code_fixer
Bitbucket
Inspects pull requests and commit diffs to identify changes that introduced issues.
🔗code_analyzer
Jira
Reads ticket context, creates investigation comments, and links root cause findings.
🔗ticketing
Linear
Integrates with Linear issues to attach investigation results and track resolution.
🔗ticketing
Shortcut
Reads stories and epics, creates comments with investigation results.
🔗ticketing
Trello
Assigns cards to CauseFlow for automated investigation with results as card comments.
🔗ticketing
Asana
Connects Asana tasks to incident investigations and posts findings as task comments.
🔗ticketing
ServiceNow
Reads incident records and CMDB context to enrich investigations with service topology.
🔗ticketing
Notion
Accesses runbooks, post-mortems, and documentation pages for investigation context.
🔗doc_enricher
Confluence
Reads internal documentation and runbooks to inform investigation hypotheses.
🔗doc_enricher
Google Docs
Retrieves relevant runbooks and design documents stored in Google Drive.
🔗doc_enricher
HubSpot
Checks customer impact, account data, and history when investigating customer issues.
Unique to CauseFlow — bridges engineering and business data.
🔗customer_bridge
Salesforce
Cross-references affected accounts and opportunities to quantify customer impact.
🔗customer_bridge
Zendesk
Correlates support tickets with production incidents to surface customer-reported patterns.
🔗customer_bridge
Intercom
Links customer conversations to technical root causes and generates customer-facing explanations.
🔗customer_bridge
PostgreSQL
Executes read-only queries to validate data state and detect anomalies during incidents.
Unique to CauseFlow — accessed via encrypted Relay with zero inbound exposure.
🔗db_analyst
MySQL
Reads table statistics and slow query logs to identify database-layer root causes.
🔗db_analyst
MongoDB
Queries NoSQL collections in read-only mode to detect data inconsistencies and performance issues.
🔗db_analyst
GitHub Actions
Correlates CI/CD pipeline runs and deployment events with incident timelines.
🔗change_detector
CircleCI
Reads build and deployment history to identify changes that triggered incidents.
🔗change_detector
Jenkins
Ingests build logs and deployment records for change impact analysis.
🔗change_detector
Argo CD
Tracks GitOps deployment syncs and rollback events across Kubernetes clusters.
🔗change_detector
REST API
Send incidents and receive investigation results via CauseFlow REST API.
🔗ingestion
Custom Webhooks
Trigger investigations from any tool using configurable inbound webhooks.
🔗ingestion
GraphQL
Query investigation results, patterns, and audit trails via the GraphQL endpoint.
🔗ingestion
AWS
Inspects ECS tasks, EC2 instances, Lambda functions, and CloudTrail events for infrastructure issues.
🔗infra_inspector
Google Cloud
Reads GKE cluster state, Cloud Run services, and audit logs to diagnose infrastructure failures.
🔗infra_inspector
Azure
Inspects Azure resource health, activity logs, and AKS clusters during incidents.
🔗infra_inspector
Kubernetes
Reads pod status, events, and resource constraints to identify container orchestration issues.
🔗infra_inspector
And many more...
We are constantly adding new integrations. Contact us if you need a specific tool.
Integration security, inherited by design
Dashboard integrations are handled by a SOC 2 Type II–certified infrastructure partner. Every OAuth flow, credential vault, and audit trail inherits their compliance posture from day one — so CauseFlow never touches raw secrets and every tool stays scoped, encrypted, and auditable.
Our integration layer is provided by a SOC 2 Type II–certified partner. All OAuth credentials, tokens, and refresh flows live inside their audited vault — covered by their attestation from the moment you connect a tool.
Credentials are encrypted with per-tenant KMS keys inside the partner vault. Secrets never land in CauseFlow application logs, CI artifacts, or error reports.
Every integration uses OAuth 2.0 with the minimum scope required. Short-lived tokens are rotated automatically; no long-lived API keys sit on our servers.
All integration credentials grant read-only access during investigations. Any write action — a PR, a runbook execution, a remediation — requires explicit human approval.
Every call the agent makes through an integration is logged: who, when, which endpoint, which scope. The trail lives in your workspace and is exportable for audits.
Credentials, tokens, and cached responses are partitioned per tenant at every layer. Cross-tenant access is architecturally impossible — not just policy-forbidden.