OBSERVABILITY◌ Research

Your ERP Integrations Failed Three Times This Month. Your Finance Team Found Out on Day Four.

Flowtaris monitors data flows between your ERP and connected systems in real time. When something breaks, the system is designed to detect it quickly — and for common known failure patterns, attempt automated remediation before your team needs to act.

Real-Time
Observability
designed to detect failures faster than manual monitoring
Fast
Failure Detection
AI-assisted anomaly detection across integration layers
Automated
Remediation
for common failure patterns — scope depends on configuration
Multiple
Integration Platforms
MuleSoft, Boomi, Azure Data Factory, Workato and more
THE INTEGRATION VISIBILITY PROBLEM

Integration failures are often invisible until they create downstream financial impact.

Enterprise finance depends on integrations between ERP systems, procurement platforms, payment systems, and reporting tools. When those integrations fail silently, the finance team often discovers the impact hours or days later. Flowtaris Integration Health Monitoring is designed to provide real-time observability across your integration layer — surfacing failures and anomalies faster than manual monitoring.

Hours
that integration failures can go undetected — creating corrupted financial data and downstream business impact.
Flowtaris AI benchmark · 200+ enterprise deployments
HOW IT WORKS

From day one to fully operational.

1
LAYER 01 — REAL-TIME MONITORING

Every data flow. Every minute. Visible in one dashboard.

Flowtaris connects to your iPaaS layer (MuleSoft, Dell Boomi, Azure Data Factory, Workato), your ERP's native integration framework, and your custom API connections. It monitors 200+ health indicators per integration — message throughput, latency, error rates, data quality scores — and surfaces anomalies within 8 minutes of occurrence.

The monitoring dashboard gives your IT and finance teams a shared, real-time view of every data flow they depend on.

  • Monitors MuleSoft, Boomi, Azure Data Factory, Workato
  • 200+ health indicators per integration per minute
  • Cross-system correlation — trace data from source to destination
  • Unified IT + finance view of integration health
Real-time integration health monitoring dashboard
Real-TimeObservability
FastFailure Detection
2
LAYER 02 — INTELLIGENT ALERTING

The right alert to the right person. Not a flood of noise.

Most monitoring tools send too many alerts — until teams start ignoring them. Flowtaris uses ML-based alert correlation to suppress redundant alerts, group related failures, and route notifications to the right person based on the system and business impact of the failure.

A failed payment file integration alerts your treasury team and your IT integration engineer simultaneously. A data quality issue in a reporting flow alerts your FP&A analyst. Nobody gets flooded.

  • ML-based alert correlation suppresses noise by 84%
  • Impact-based routing: financial vs. operational vs. IT alerts
  • PagerDuty, Slack, and Teams native integrations
  • Business-context alerts: "AP payment run will fail in 2 hours"
Intelligent alert routing and notification management
AutomatedRemediation
MultipleIntegration Platforms
3
LAYER 03 — AUTO-REMEDIATION

73% of integration failures fixed before your team sees them.

Flowtaris maintains a library of 400+ remediation playbooks for common integration failure patterns — connection timeouts, schema mismatches, authentication token expiry, message queue backlogs. When a known failure pattern is detected, the appropriate playbook executes automatically.

For novel failure patterns, Flowtaris generates a suggested remediation and routes it to your integration engineer with one-click approval.

  • Maintains a library of remediation playbooks for common integration failure patterns
  • Designed to auto-remediate known failures — scope depends on configuration and environment
  • Schema drift detection and auto-mapping capabilities
  • Full remediation audit log for post-incident review
Auto-remediation execution log and playbook library
TECHNICAL ARCHITECTURE

Enterprise-grade from the ground up.

ComponentTechnology
Monitoring AgentLightweight monitoring agent
Anomaly DetectionML-based anomaly detection
Remediation EngineDecision tree + LLM Reasoning
Alert CorrelationGraph-based event correlation

Connects to the stack you already run.

No rip-and-replace. No new modules. Flowtaris layers on top of your existing ERP investment.

MuleSoftDell BoomiAzure Data FactoryWorkatoNetSuiteCoupaSAPWorkdayPagerDutyDatadogSplunkServiceNow
FAQ

The questions your board will ask. Answered.

How does Flowtaris connect to our existing integration middleware?
Flowtaris uses a lightweight monitoring agent that deploys alongside your existing middleware — MuleSoft, Boomi, Workato, Azure Data Factory, or custom Node.js/Python integration services. The agent captures metrics via standard observability interfaces (OpenTelemetry, Prometheus, vendor APIs) and does not require changes to your integration code. Deployment takes 2-4 hours per integration platform.
What is the performance impact of the monitoring agent?
The Flowtaris monitoring agent is built in Go and uses eBPF kernel probes where available to capture metrics with near-zero overhead. In production benchmarks, the agent adds <0.1% CPU overhead and <50MB memory consumption on the host system. Network overhead for telemetry transmission is <2MB per hour per monitored integration.
How does auto-remediation work and what actions can it take?
Auto-remediation executes from a library of pre-approved playbooks. Common automated actions include: restarting a failed integration flow, clearing a blocked message queue, refreshing an expired OAuth token, reallocating a connection pool, or reprocessing a failed batch from the last successful checkpoint. Destructive actions (deleting records, truncating queues) are never automated — they always require human approval.
Can Flowtaris detect data quality issues, not just infrastructure failures?
Yes — data quality monitoring is a first-class capability. Flowtaris compares data volumes, field completeness, format consistency, and referential integrity across integration checkpoints. If an integration is flowing data but 30% of invoice records are missing a required GL code, that data quality anomaly is flagged as a warning before it causes downstream ERP posting failures.
How does this integrate with our existing IT incident management process?
Flowtaris integrates natively with ServiceNow, Jira Service Management, PagerDuty, and OpsGenie for incident creation and management. When Flowtaris creates an incident, it includes the full diagnostic context — which integration failed, what data was affected, the remediation steps attempted, and the business impact assessment. This dramatically reduces MTTR by eliminating the diagnosis phase of incident response.

Do you know the current health status of every ERP integration you depend on?

Most finance and IT teams don't — until something breaks. Run our integration risk assessment and see your exposure in 15 minutes.

Flowtaris AICapabilitiesIntegration Health Monitoring