Unified Pipeline-to-AI architecture
FFWD Pipeline collects from all sources in any format, processes at AI-scale volume, and routes to any destination. At the aggregation point—before data silos off to downstream systems—FFWD Correlation has the cross-domain visibility to detect what siloed monitoring tools can't. Correlation is inherent to the telemetry pipeline—it's the only point that sees everything.
Telemetry Pipeline
FFWD-UC : Universal Collectors
Lightweight collectors deployed at edge and remote locations. Docker containers or Kubernetes pods. Collect and parse at source before forwarding to central cluster.
FFWD-DC : Data Cluster
Centralised processing for enrichment, transformation, and intelligent routing. Scale linearly to handle any rate and volume.
Notable pipeline features :
Effortlessly scale to Millions logs per second scale on 4 x virtual machines
AI assisted : complex parsing, transform, enrichment, log routing operations in-flight
Ship to any destination of choice (Splunk, Datadog, Elastic, Kafka, S3 and more)
Reduce data volume by more than 50% before expensive destinations
Full Rust Data Path
Entire data path of FFWD is built on Rust, highest performance from collection to external destinations, & our internal Datafusion based databases and storage.
Some supported data sources :
AMQP · Apache Metrics · AWS ECS Metrics · AWS Kinesis Firehose · AWS S3 · AWS SQS · dnstap · Docker Logs · EventStoreDB Metrics · File · Fluent · GCP PubSub · GNMI · Heroku Logplex · Host Metrics · HTTP Client · HTTP Server · JournalD · Kafka · AWS MSK · Kubernetes Logs · Logstash · MongoDB Metrics · MQTT · NATS · NGINX Metrics · OpenTelemetry · PostgreSQL Metrics · Prometheus Remote Write · Prometheus Scrape · Redis · Socket · Splunk HEC · StatsD · Stdin · SNMP Trap · SNMP Get · Syslog · Syslog UDP · ~100 Grok Templates · NVIDIA GPU · Intel · AMD · Huawei · Broadcom · Apple · Qualcomm GPU · Custom Formats
Some supported data Destinations :
AWS S3 · AWS CloudWatch Logs · AWS CloudWatch Metrics · AWS Kinesis Streams · AWS Kinesis Firehose · AWS MSK · AWS SQS · Azure Blob · Azure Monitor · Google Cloud Storage · Google Cloud Pub/Sub · Google BigQuery · Kafka · Splunk HEC · Datadog Logs · Datadog Metrics · Datadog Traces · Elasticsearch · OpenSearch · OTLP · Loki · InfluxDB · Prometheus Remote Write · ClickHouse · Coralogix · Redis · New Relic · Honeycomb · Axiom · Mezmo · Sumo Logic · Chronicle · Papertrail · NATS · Pulsar · AMQP · HTTP · Syslog · Socket
Anomaly Correlation
Detection Engine
Blank-slate approach: auto-discover, auto-extract, auto-detect, auto-correlate
No biased human input required
In-house transformer AI for sequence and semantic analysis
Multiple detection models: log structure, spikes, forecasting, drift, clustering, sequence, semantic.
Correlation
Marker-based scoring system tracks anomalies over time
Cross-domain correlation surfaces connected issues
Detects slow-morphing, non-obvious problems
Agentic Root-Cause
Integrates latest LLMs: Claude, OpenAI, DeepSeek, Mistral
Troubleshooting agent with multi-modal knowledge base (PDF, TXT, JSON, PNG)
Evidence-based advisory Sub-agents
Model Context Protocol (MCP) Integration
AIOps isn't one AI system—it's many. Different agents for different tasks, different teams, different use cases. MCP provides the standard interface that lets any of them access your operational data without custom integration work. FFWD is the data layer that powers them.
Built-in MCP server for external AI agents
Exposes anomaly reports, symptoms, evidence memories, correlation journals, raw logs and metrics
Supports Claude, ChatGPT, Copilot, custom agents
Private Deployment
FFWD Pipeline 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 ready—run as private SaaS for multiple business units or subsidiaries