See infrastructure fail before production does
Design, simulate, monitor and predict infrastructure behavior before outages happen. SystemFlow turns architecture into a living model you can stress-test, observe, and trust.
Part of the GigPlux product family
One model for the entire lifecycle of your infrastructure
Design, simulation, observability, and intelligence converge in a single system of record - so the diagram, the runtime, and the incident all speak the same language.
Infrastructure Designer
Compose systems from a typed node library. Every diagram is an executable model, not a static picture.
02Traffic Simulation
Replay production-grade load and watch where latency, saturation, and retries accumulate.
03Failure Prediction
The ML engine models normal behavior and flags the conditions that precede outages.
04Root Cause Analysis
Collapse a noisy incident into a single causal chain, ranked by contribution.
05AI Architecture Review
Automated design critique against reliability, scaling, and security best practices.
06Real-Time Monitoring
Live signals streamed over websocket, mapped directly onto the topology you designed.
Your architecture, as a living diagram
Map every service, dependency, and edge into a single canvas that stays in sync with reality. Trace blast radius and understand exactly what breaks when one node goes down.
- Typed node library spanning compute, data, network, and edge
- Dependency mapping from your own topology
- Blast-radius highlighting for any failure scenario
Stress-test before the load arrives
Replay realistic traffic patterns against your topology and watch where latency, saturation, and retries pile up - long before a real spike finds the weak point for you.
- Configurable synthetic load generation
- Saturation and cascade detection across your topology
- Re-run the same scenario after every change
A staff engineer's review, on every design
SystemFlow evaluates your architecture against reliability, scaling, and security best practices - then scores and explains each finding so you know exactly what to fix first.
- Risk-scored findings with severity and rationale
- Reliability, scaling, cost, and security dimensions
- Actionable remediation tied to your topology
Collapse the war room into one screen
When something breaks, SystemFlow assembles the causal chain automatically - correlating deploys, metrics, and dependencies into a single ranked explanation.
- Automated causal chains across services
- Deploy and change correlation
- Confidence-ranked contributing factors
- 14:02:11Config change deployed
- 14:02:48Connection pool exhausted
- 14:03:20Orders latency ▲ 4.2s
- 14:03:55Checkout error rate 18%
Observability that knows what normal looks like
Stream live signals from every service and edge, with anomaly detection that models baseline behavior and surfaces the conditions that precede an incident.
- Live metric streaming over websocket
- Baseline-aware anomaly detection
- One model for design and monitoring
130 component types, and counting
Everything from a browser to a GPU cluster, each with its own behaviour under load. The 22 newest are reserved in the library while their simulation behaviour is built - visible and searchable, marked Coming Soon, and not gated behind any plan.
Pay for the compute you actually use
Simulation runs and AI analysis draw from a credit balance instead of a flat fee. Designing, editing and opening your work stays free - credits meter the compute, not your architecture.
A balance, not a meter you cannot see
Your credit balance sits in the header while you work and opens the wallet in one click, so a run never costs you something you did not know about.
Coupons redeem instantly
Enter a credit code and the balance updates before the dialog closes. Codes can be single-use or shared across a team.
Every movement is on the record
Grants, coupons, spends and refunds all land in a ledger you can read back, so a charge can always be traced to the run that caused it.
A failed run refunds itself
Charges settle before the work starts and anything that errors returns the credits automatically. Concurrent runs can never overdraw a balance.
A small team with one clear direction
“Every major outage is obvious in hindsight. SystemFlow exists to make it obvious in advance - model the system, break it in simulation, and fix it before production ever sees it.”
“We build focused software that earns its place. SystemFlow does one thing completely: it shows you how your infrastructure fails before your users do.”
Start free. Scale when production demands it.
Transparent plans for every stage - from a solo architect modeling a side project to a global SRE org running mission-critical systems.
For individuals modeling and simulating a single system.
- 1 workspace, 1 environment
- Infrastructure Designer
- Traffic simulation
- AI architecture review (chat)
- 7-day metric retention
For engineering teams running production workloads.
- Unlimited environments
- Real-time monitoring
- Anomaly detection & root cause analysis
- AI architecture reviews
- 90-day retention
- Role-based access control
For organizations that need custom terms and support.
- Unlimited usage & seats
- Custom data retention
- A direct line to the team building the product
- Invoiced billing available on request
Engineered to the standard of the systems it protects
SystemFlow is in beta - we do not claim certifications we have not earned yet. Here is our real security posture, stated plainly.
Security-first engineering
Hardened backend: strict CORS, CSP, rate limiting, constant-time secret checks, and audited dependencies.
Encryption everywhere
TLS everywhere in transit and encrypted storage at rest through our infrastructure providers.
Privacy by default
We collect only what the product needs, never sell data, and purge deleted accounts within 90 days.
Self-hosting on the roadmap
Docker-based self-hosting is part of the plan, so your telemetry can stay inside your boundary.
Find the outage in simulation, not in production.
Model your infrastructure, stress it until it breaks, and ship with the confidence that you have already seen what fails.