LogoFLARE
IntelsatSatellite Operator
SES NetworksSatellite Operator
National GridGrid Utility
Hydro-QuébecGrid Utility
Lufthansa SystemsAviation
IATAAviation
Munich ReInsurance
Swiss ReInsurance
EutelsatSatellite Operator
Elia GroupGrid Utility
Air Navigation ProAviation
DLRDefense / Research
IntelsatSatellite Operator
SES NetworksSatellite Operator
National GridGrid Utility
Hydro-QuébecGrid Utility
Lufthansa SystemsAviation
IATAAviation
Munich ReInsurance
Swiss ReInsurance
EutelsatSatellite Operator
Elia GroupGrid Utility
Air Navigation ProAviation
DLRDefense / Research
Live Feed Active

Operational intelligence for satellite operators, grid engineers, and aviation planners who can't afford to wait for the next news cycle.

flare.systems / dashboard / live
CONNECTED
Kp Index
4.3
+0.8 / 1hActive — watch conditions
Solar Wind
612km/s
+48 / 3hAbove quiet threshold
Proton Flux
1.4pfu
−0.1 / 1hBelow ICAO threshold
Dst Index
−38nT
−12 / 2hModerate ring current
Sources: NOAA SWPC · ESA SSA · DSCOVR L1 · ACERefresh: 60s
Scroll through evidence
Spoke 01

Data Sources

Seventeen real-time magnetometer networks, three L1 solar wind monitors, and direct ACE/DSCOVR telemetry — ingested in parallel, cross-validated before any alert fires.

How It Works

Multi-Source Ingestion with Cross-Validation

Every alert begins with raw magnetometer readings from 17 globally distributed ground-based networks, fused with L1 solar wind data from ACE and DSCOVR satellites. Before any processed output leaves the pipeline, a voting consensus across independent source sets must agree within ±8% on Kp magnitude. Single-source alerts — the norm at legacy providers — are rejected outright. This cross-validation step alone reduces false positives by 73% compared to single-feed systems.

17×
More source networks than single-feed providers
Data Pipeline
Ingest
Raw Magnetometer + L1 Telemetry
17 networks, 60-second cadence
Validate
Cross-Source Consensus
±8% agreement threshold
Fuse
Weighted Data Fusion
Source quality scoring
Normalize
Calibrated Output
IAGA-compliant units
Side-by-side comparison
Metric
Flare
Industry Std.
Legacy Providers
Ground magnetometer networks
17 networks
4–6 networks
1–2 networks
L1 solar wind monitors
ACE + DSCOVR + WIND
DSCOVR only
NOAA relay (delayed)
Data cadence
60-second
5-minute
15–60 minute
Cross-source validation
Automated consensus
Manual QC
None
False positive rate
3.2%
12–18%
22–31%

Data sourced from independent benchmark studies and internal validation logs. Last updated Feb 2026.

Spoke 02

Forecast Models

Three independently validated ensemble models — ENLIL solar wind propagation, custom Kp neural regression, and CME trajectory Monte Carlo — run in parallel and reconciled before any forecast is issued.

How It Works

Ensemble Modeling with Hindcast Validation

The Kp forecast pipeline runs three models simultaneously: a physics-based ENLIL solar wind propagation model, a gradient-boosted neural network trained on 22 years of NOAA historical data, and a Monte Carlo CME trajectory ensemble with 1,000 particle simulations per event. Final forecasts are a skill-weighted average of all three outputs. Every model is validated monthly against 6-month hindcast windows. Skill scores are published in the Accuracy Report.

0.87
Heidke Skill Score — top decile for operational Kp forecasting
Data Pipeline
Model A
ENLIL Propagation
Physics-based solar wind
Model B
Neural Kp Regressor
22yr training corpus
Model C
CME Monte Carlo
1,000 trajectories/event
Ensemble
Skill-Weighted Fusion
Published Heidke score
Side-by-side comparison
Metric
Flare
Industry Std.
Legacy Providers
Forecast horizon
72-hour deterministic + 7-day probabilistic
48-hour deterministic
24-hour, single model
Modeling approach
Ensemble (3 models)
Single physics model
Statistical climatology
Heidke Skill Score
0.87
0.61–0.68
0.38–0.52
CME trajectory modeling
Monte Carlo 1,000-particle
Cone model
Not available
Hindcast validation cadence
Monthly, published
Annual, internal
Not published

Data sourced from independent benchmark studies and internal validation logs. Last updated Feb 2026.

Spoke 03

Alert Latency

From magnetometer anomaly detection to webhook delivery in under 90 seconds. Measured, published, and contractually guaranteed at the 95th percentile.

How It Works

Sub-90-Second Detection-to-Delivery Pipeline

Latency is measured from the moment an upstream sensor crosses the alert threshold to the moment the first webhook fires at the client endpoint. The pipeline is fully event-driven: no polling loops, no batch jobs. Alert generation runs on dedicated compute isolated from the analytics workload, ensuring that dashboard traffic never delays operational alerts. P95 latency is contractually guaranteed at <90 seconds for Kp threshold breaches and <4 minutes for CME impact predictions.

<90s
P95 detection-to-delivery latency, contractually guaranteed
Data Pipeline
Detect
Threshold Breach
Event-driven, no polling
Classify
Alert Severity
G1–G5, S1–S5, R1–R5
Route
Delivery Queue
Isolated compute path
Deliver
Webhook / SMS / Email
P95 < 90s, contractual
Side-by-side comparison
Metric
Flare
Industry Std.
Legacy Providers
P50 alert latency
34 seconds
4–8 minutes
15–45 minutes
P95 alert latency
88 seconds
12–18 minutes
30–90 minutes
Contractual SLA on latency
Yes, P95 guaranteed
Best-effort
Not offered
Alert pipeline isolation
Dedicated compute
Shared workload
Batch processing
Historical latency logs
Full audit trail, exportable
Summary only
Not available

Data sourced from independent benchmark studies and internal validation logs. Last updated Feb 2026.

Spoke 04

Integration

REST API, webhook callbacks, MQTT for IoT environments, email digests with structured metadata, and SMS/voice escalation for on-call engineers. All delivery methods are active simultaneously.

How It Works

Multi-Channel Redundant Delivery

Critical operational alerts should never depend on a single delivery channel. Flare delivers every alert simultaneously across all configured channels, with per-channel acknowledgment tracking. If a webhook endpoint fails to return HTTP 200 within 10 seconds, the system escalates automatically to the backup channel. Integration takes under 20 minutes for most operational teams: a REST API key, one webhook endpoint, and one email address is all that's required to go live.

18 min
Median time from API key issuance to first live alert received
Data Pipeline
API
REST + MQTT
JSON, OAuth2, OpenAPI 3.1
Webhook
Callback Delivery
Signed payloads, retry logic
Email
Structured Digest
HTML + plain text, metadata
Escalate
SMS / Voice
Auto-escalate on ACK timeout
Side-by-side comparison
Metric
Flare
Industry Std.
Legacy Providers
API protocol
REST + MQTT + WebSocket
REST only
FTP / email only
Simultaneous delivery channels
All channels, parallel
Primary only
Single channel
Webhook failure escalation
Automatic, <10s
Manual retry
Not available
Integration time (median)
18 minutes
2–5 days
1–3 weeks
OpenAPI documentation
Full spec, versioned
Partial
PDF only

Data sourced from independent benchmark studies and internal validation logs. Last updated Feb 2026.

Spoke 05

Pricing & Parallel Test

You've seen the pipeline, the models, and the benchmarks. Now run both systems simultaneously for 14 days. Zero commitment. Full operational data.

Operational
$2,400/mo

Single sector, up to 5 alert recipients.

  • 3 data streams included
  • 72-hour Kp forecasts
  • API + email delivery
  • 99.5% uptime SLA
  • Email support (4h SLA)
Most Selected
Mission-Critical
$7,800/mo

Multi-sector, unlimited recipients.

  • All data streams
  • 7-day probabilistic forecasts
  • All delivery channels
  • 99.95% uptime SLA
  • Dedicated operations contact
  • Custom threshold configuration
Enterprise
Custom

On-premise option, custom integrations, white-label.

  • Everything in Mission-Critical
  • On-premise deployment option
  • Custom model calibration
  • White-label API available
  • Dedicated SRE team
Primary Path

Run a Parallel Test

Receive both your current provider's alerts and Flare's simultaneously for 14 days. Compare latency, accuracy, and coverage in your actual operational environment.

No credit card. No contract. Operational data only. We don't share provider names.

Secondary Path

Download the Accuracy Report

48 pages. 24 months of hindcast validation across 3,200 geomagnetic events. Model skill scores, false positive rates, and latency distributions by event class.

Flare_Accuracy_Report_2026.pdf
48 pages · 3.2 MB · Updated Feb 2026
0.87
Kp Skill Score
3.2%
False Positive Rate
3,200
Events Analyzed

Instant delivery. No sales follow-up unless you ask.