Conecte toda sua stack
CauseFlow integra com suas ferramentas existentes — monitoramento, código, bancos de dados e suporte ao cliente. Cada uma mapeada para um agente de IA especializado.
Catálogo de Integrações
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
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
E muito mais...
Estamos constantemente adicionando novas integrações. Entre em contato se precisar de uma ferramenta específica.
Segurança das integrações, herdada por design
As integrações do dashboard passam por um parceiro de infraestrutura certificado SOC 2 Tipo II. Cada fluxo OAuth, vault de credenciais e trilha de auditoria herda a conformidade dele desde o primeiro dia — o CauseFlow nunca toca em segredos brutos e toda ferramenta fica escopada, criptografada e auditável.
A camada de integrações é provida por um parceiro certificado SOC 2 Tipo II. Credenciais OAuth, tokens e refresh flows ficam dentro do vault auditado dele — cobertos pela atestação no momento em que você conecta uma ferramenta.
Credenciais são criptografadas com chaves KMS por tenant dentro do vault do parceiro. Segredos nunca caem em logs de aplicação, artefatos de CI ou relatórios de erro do CauseFlow.
Cada integração usa OAuth 2.0 com o escopo mínimo necessário. Tokens de curta duração são rotacionados automaticamente; nenhuma API key de longo prazo fica nos nossos servidores.
Todas as credenciais de integração concedem acesso somente leitura durante as investigações. Qualquer ação de escrita — um PR, execução de runbook, remediação — exige aprovação humana explícita.
Toda chamada que o agente faz via integração é registrada: quem, quando, qual endpoint, qual escopo. A trilha vive no seu workspace e é exportável para auditorias.
Credenciais, tokens e respostas em cache ficam particionados por tenant em cada camada. Acesso cruzado é arquiteturalmente impossível — não apenas proibido por política.