Bring infrastructure intelligence directly to the AI agents you already use today.
FFWD delivers assurance gating, anomaly correlation and cross-domain telemetry directly to your AI agent. No new dashboard. No new agent. No platform migration.
From today's human driven AI Apps, to full autonomous agents of the future.
Infrastructure agents fail in ways nobody is watching for.
AI agents acting on production infrastructure don't fail with errors. They improvise — route around constraints, retry with workarounds, find alternate paths. From the inside it looks like normal operation: no errors, reasonable latency. From the outside, an infrastructure agent pushes a config change that isolates a data centre. It scales the wrong service and burns through cloud budget in an hour. It restarts a database during peak load. It mis-provisions network capacity and breaches SLAs across thousands of customers at once.
Today's AI safety watches what agents say. Almost nobody watches what agents do to the infrastructure they're acting on — or whether that infrastructure was stable enough to act on safely. The clues aren't inside the agent. They're scattered across the operations stack the agent lives in.
FFWD answers one question for every infrastructure agent: is it safe to let this agent act right now?
When the answer is no, FFWD blocks the next action before it executes.
Agent Assurance. Infrastructure Intelligence. Telemetry Pipeline. Unified by design.
Nio Agent Assurance
The Go/No-Go gate from today's AI apps to tomorrow's autonomous agents.
Infrastructure agents do not always fail with obvious errors. They improvise: workarounds, create scripts, alter target systems to fit, and scaling decisions that can look normal from inside the agent while damaging production outside it.
FFWD watches what agents do to infrastructure, not just agent actions. It combines agent behaviour, live stack health, and action criticality into a real-time Execution Risk Score before each critical action runs.
FFWD Anomaly Engine
Cross-domain anomaly correlation and detection
An extensive AI/ML toolbox evaluates every dimension of your telemetry simultaneously — structural, sequence, semantic, drift, spike, and clustering. Then correlates across all of them to surface causal chains that span Agents, GPU, network, container, application, and infrastructure layers.
Root-cause advisory reports synthesise findings into natural language with symptomatic log evidence. Delivered to humans or directly to AI agents via MCP.
Explore Anomaly Correlation →FFWD Pipeline
High Performance Telemetry Pipeline
Collect natively from every layer of your stack — Agents, GPU, network, container, application — at AI scale, without gaps. Parse, transform, enrich, and reduce in-flight, then route to any combination of destinations.
Built on Rust, deployed privately, with pricing that doesn’t scale with your data. The data foundation that FFWD’s anomaly engine and agent assurance both run on.
Explore Telemetry Pipeline →Headless infrastructure intelligence, delivered where your AI agents already work.
FFWD exposes assurance verdicts, anomaly findings, telemetry, and pipeline configuration through a built-in MCP interface. No new dashboard for the agent. No copied context. The operational state becomes queryable and actionable inside Claude, Copilot, GPT, Codex, or your own infrastructure agent.
Execution Risk Scores
Agents can ask whether a critical action is safe before it runs.
Root-cause advisory
Findings, journals, correlations, and evidence arrive as agent-readable context.
Telemetry + configuration
Query logs and metrics, then parse, transform, and route data through plain-language workflows.
Claude, GPT, Gemini, Grok, Copilot.
Claude Code, Codex CLI, OpenClaw, custom tool-calling agents.
On-prem and air-gapped LLM workflows stay inside your environment.
One interface for every operational question.
Ask for risk, root cause, raw telemetry, current pipeline state, or safe next steps without switching tools.
- Pre-action Go/No-Go verdicts
- Symptomatic logs and causal chains
- Collector, parser, transform, and routing configuration
Agent-readable, human-governed.
MCP gives agents the context to act. FFWD keeps the data private, auditable, and enforceable inside your perimeter.
Three layers. One MCP interface. Any AI app or agent.
Pipeline collects. Intelligence correlates. Assurance gates. All three exposed to whichever AI app your team already uses — Claude, Copilot, GPT, or your own infrastructure agent.
Assurance Layer — Nio Agent Guard
The Go/No-Go gate at the action moment.
Nio sits in the agent's action path. An Execution Risk Score combines agent behaviour, full-stack infrastructure health, and the blast radius of the proposed action — into one quantitative verdict, delivered to your AI app through API before every critical action.
When the score crosses your policy threshold, Nio gates the next action: blocked, confirmed by a human, or allowed. After execution, the Intelligence Layer correlates impact and feeds it back to the score. Pre-action restraint and post-action learning, in one closed loop.
Intelligence Layer
Anomalies, correlation, root cause — across everything.
Eight ML model families run across silicon, network, application, and agent behaviour simultaneously, then correlate across them to surface causal chains.
Findings arrive as a natural-language root-cause advisory — readable by your engineers through Claude, or consumed directly by your infrastructure agents through MCP. The same correlations feed the Assurance Layer's risk score above. No rule libraries to maintain. No alert tuning to keep current.
Data + Pipeline Layer
The foundation everything sits on. Silicon-to-semantic.
A Rust-native pipeline scaling linearly to millions of events per second across 50+ connectors — GPU metrics, Kubernetes, SNMP, Kafka, OpenTelemetry, Syslog, and more. Forwards in parallel to whichever destinations you already use: Datadog, Elastic, Kafka, S3, Splunk, OpenSearch, Azure Blob, GCS.
Deploys where your data lives.
FFWD runs entirely inside your perimeter: on-prem, private cloud, or air-gapped. Telemetry, risk scores, anomaly evidence, and pipeline configuration stay under your control, with no external SaaS dependency.
On-premises
Run close to production systems, sensitive telemetry, and regulated workloads.
Private cloud
Deploy into your cloud accounts and network boundaries without shipping data out.
Air-gapped
Support isolated environments where external callbacks and SaaS control planes are not acceptable.
Multi-tenant
Serve teams, sites, or customers from one deployment while preserving data isolation.
Deploys where your data lives.
Private. On-premise. Air-gapped. Your telemetry never leaves your environment.
FFWD runs entirely inside your perimeter — on-prem, private cloud, or air-gapped. No telemetry leaves your environment. No external SaaS dependency. Built for enterprises where data sovereignty and regulatory compliance are the starting point, not an option.
“We, SAKURA internet, Inc., is constantly pursuing innovations to help our customer’s business run more efficiently and smoothly.
We are very honoured to contribute their success by offering FFWD, a superior observatory services on our IaaS service, “SAKURA’s Cloud” , (so-called, Logging as a Service) provided in SaaS format through this partnership.”
“Capabilities such as infrastructure self-recovery and fast time to restoration after failure are very important to our business. Logs and events are essential clues and triggers to achieving these capabilities. FFWD helps us to affordably collect, analyse and monitor our infrastructure logs and events in real-time, improving our operational reliability and efficiencies.”