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
Our integration infrastructure is independently audited and certified to meet the highest security standards for enterprise data access.
Our integration infrastructure holds SOC 2 certification — ensuring your credentials and data access patterns meet independent security audit standards.
ISO 27001:2022 certification for our integration infrastructure confirms that information security management meets the latest international standard.
All integrations use OAuth 2.0 where supported. API keys are encrypted at rest with per-tenant keys and never exposed in logs or responses.
Integration credentials are stored with AES-256 encryption using per-tenant KMS keys. No credential is ever stored in plaintext.
Every integration operates in read-only mode during investigations. Write operations — such as opening a fix PR — require explicit human approval.
Integration credentials and access tokens are strictly isolated per customer. No cross-tenant data access is possible at any layer.