AI Anomaly Correlation
Cross-domain detection that siloed monitoring tools can't achieve. FFWD Correlation uses in-house deep learning to detect slow-morphing, non-obvious issues across your entire stack—before they cascade into incidents.
Monitoring tools only see their own slice
Splunk sees security logs. Datadog sees APM traces. Your network tools see packets. None of them can correlate across domains because none of them have the full picture.
The hardest problems—the ones that wake you up at 3am—are cross-domain. A network issue manifests as application latency. A network flapping event causes model inference timeouts. These connections are invisible to siloed tools
Pipeline Sees Everything Before the Silos
FFWD Pipeline aggregates telemetry from your entire stack before routing it to downstream systems. That aggregation point is the only place in your architecture with a complete cross-domain view.
Correlation is what becomes possible when you have visibility across hardware, network, orchestration, and workload layers simultaneously.
Comprehensive suite of in-house AI and ML models
Auto-extract markers from raw logs and metrics
Evaluate anomalies using transformer-based models
Track markers over time to detect drift and slow-morphing changes
Correlate across domains to surface connected symptoms
Agentic root-cause advisory powered by latest LLMs
Are your AI Agents Behaving ?
AI agents are the top use case for LLMs—and the hardest to monitor. They perform autonomous tasks, make autonomous decisions, and their behaviour can drift over time.
FFWD tracks agent behaviour profiles:
Tool use patterns shifting
Prompt/response profiles changing
Token counts deviating
Response times drifting
Internal data access patterns changing
Model Context Protocol (MCP) Integration
FFWD's built-in MCP server exposes anomaly detection data and correlation reports directly to AI agents. Your can use your preferred AI apps such as Claude or Co-Pilot to help troubleshoot issues or analyse patterns.
In addition to anomaly detection symptoms and patterns, FFWD MCP server exposes raw logs and metrics for free-form queries—AI agents can dig deeper when they need to, running their own analysis against your telemetry database. All within your security perimeter.
Private Deployment
FFWD Anomaly Correlation runs entirely within your environment. On-premises, private cloud, or air-gapped—your telemetry never leaves your security perimeter. No SaaS dependencies. No data sovereignty concerns. Multi-tenant architecture lets you run FFWD as private SaaS—serving multiple business units from a single deployment with full data isolation.