IgnisVision is a planetary-scale SaaS platform that utilizes AWS Ground Station and SageMaker to detect wildfires from orbit in under 15 minutes. It leverages Amazon Bedrock to instantly turn raw thermal data into localized, plain-language alerts for first responders, bypassing technical jargon when every second counts. Optimized with Inferentia2 for cost-efficiency, the platform provides a global, zero-infrastructure solution that meets the highest AWS AI Competency standards. This approach empowers governments to halt "megafires" before they start, significantly reducing both carbon emissions and disaster management costs.

IgnisVision

Planetary Orbital Intelligence

When a forest burns, every second is a hectare lost.

Traditional ground-based monitoring is no longer enough for global environmental protection. This is where IgnisVision steps in—an automated AWS-native workflow that detects threats before they become catastrophes.

1. The Economics

Covering remote biomes with ground sensors is a logistical nightmare. To monitor a single national park, you need thousands of devices and constant maintenance.

Traditional Model High CAPEX (hardware) and OPEX (maintenance). You pay for sensors that might never see a fire, but still require batteries and repairs.

IgnisVision (AWS-Native) Zero ground infrastructure. By using AWS Ground Station, you downlink data from existing LEO satellites and pay only for the minutes of data ingested and processed.

TCO Reduced by up to 55%

2. Planetary Scalability

A single watchtower can see for 10 miles. A satellite constellation sees the entire planet. IgnisVision monitors the Amazon, the Taiga, and the Australian Outback simultaneously using SageMaker Multi-Model Endpoints.

Detection to Action Latency:

Manual / Ground Method ~2 Hours

IgnisVision (AI + Space) < 15 Min

Result: Excellent chance of suppression vs. high chance of "Megafire".

3. Strategic Intelligence

AI identifies the "what" and "where," but humans decide the "how." IgnisVision leverages Amazon Bedrock to bridge the gap between complex data and field action:

Automated SITREPs: Responders receive natural language reports: "High-intensity fire detected 2km from Sector B. Wind gusting North-East. Recommend immediate deployment."
Filtering Noise: The AI model (Genesis) filters out false positives like industrial heat or controlled burns, ensuring experts deal only with real emergencies.
The Hybrid Model: AI provides the planetary-scale "Eyes," freeing human specialists to focus on high-level evacuation strategies.

4. Zero-Infrastructure Deployment

Governments can activate IgnisVision in hours, not months. There are no towers to build or drones to pilot.

"A remote community in the Mediterranean is now protected by the same orbital tech as the Amazon rainforest, delivered via a single AWS CloudFront dashboard."

Summary: Planetary-Scale Protection

IgnisVision stops the search and starts the response. We stop paying for manual surveillance and start investing in immediate, data-driven suppression that saves lives and the climate.