Geospatial Development, Unified.

Geospatial development has historically been plagued by fragmentation. Engineers and data scientists had to string together disparate tools for image sourcing, tiling, annotation, model training, and web-visualization.

MinerAI (developed by Xuremi Inc.) solves this by uniting the entire pipeline into a single, high-performance computing stack. Originally built as a specialized machine learning system for detecting unlicensed artisanal mining excavation, MinerAI has evolved into a general-purpose Earth observation infrastructure.

Today, our backend interfaces directly with major satellite imagery constellations, pulling optical, multi-spectral, and synthetic-aperture radar telemetry. By pairing this data with automated tiling processes and deep learning models (such as regularized U-Net architectures with ResNet34 backbones), we translate raw orbital streams into structured GeoJSON vectors and real-time environmental alerts in under 67 seconds per 100 km².

10M+
Hectares Monitored
150K+
Masks Processed
66.7s
Inference per 100 km²
24/7
Uptime Reliability
Use Cases

Built for Production

From regulatory oversight to environmental intelligence and precision agriculture.

01. Regulatory Mining Oversight

Enables government authorities and compliance teams (like Kenya Mining Watch) to actively scan expansive territories, automatically segment artisanal mine footprints, and pinpoint exact excavation coordinates for ground verification.

02. Ecological Preservation

Quantifies environmental damage in real-time. Automatically tracks deforestation rates, monitors tailings dam erosion, identifies unauthorized land-use changes, and maps ecological degradation across critical biospheres.

03. Precision Agriculture

Leverages multi-spectral and thermal band analysis to inspect crop health, predict potential crop yields, identify agricultural blights early, and flag irrigation anomalies across thousands of hectares simultaneously.

04. Disaster & Hazard Tracking

Monitors regional anomalies to direct disaster response. Detects active flooding, river widening, structural mudslide risks, and conflict-driven land changes to protect vulnerable local communities.

The Stack

The Architectural Layers

A deep look into the backend systems that orchestrate our Earth intelligence platform.

Data Engineering & Storage

Leverages S3-compatible cloud storage (DigitalOcean Spaces) with presigned secure token exchanges. Automatically manages image ingestion, tile division, and versions training datasets.

Model Architecture & HF Distribution

Integrates PyTorch U-Net models featuring ResNet34 backbones with regularized dropout layers. Model checkpoints are securely managed and pulled from Hugging Face model repositories.

Multi-Threaded Orchestration

Powered by a pooled Python backend (utilizing ThreadPoolExecutor with 50 concurrent worker allocations) to manage database interactions, concurrent tiling tasks, and API proxying.

Developer API & Rate Limits

Exposes RESTful endpoints protected by cryptographically secure API keys. Throttles concurrent requests, limits data download threads, and logs usage metrics to ensure service stability.

The Engine

The Closed Intelligence Loop

Our platform closes the gap between raw data and real-world compliance through a self-reinforcing intelligence loop.

STEP 01

Ingestion

Automated ingestion of raw satellite imagery based on bounding coordinates.

STEP 02

Preprocessing

Splitting tiles, normalizing bands, and caching GeoTIFF imagery.

STEP 03

AI Inference

U-Net models generate segmentation masks to identify targets.

STEP 04

Verification

Users review detections, log incidents, and export GeoJSON annotations.

STEP 05

Retraining

User corrections update training sets, triggering model retraining.

The MinerAI Ethos

Guided by core principles ensuring our technology remains open, verifiable, and entirely focused on preserving the biosphere.

Radical Transparency

We firmly believe environmental data must be a public good. Our commitment to open model weights and verifiable segmentation logic ensures spatial intelligence remains objective, democratized, and fully accessible to all global stakeholders.

Precision Engineering

In geospatial analysis, a minor margin of error dictates the survival of protected ecosystems. We rigorously optimize our architecture's signal-to-noise ratio, offering regulators irrefutable data for definitive legal or environmental action.

Sovereign Infrastructure

Our systems are architected to empower individual nations and localized communities. The MinerAI ecosystem is built to be deployed seamlessly across distributed grids, guaranteeing total data sovereignty for the regions we serve.

Biosphere First

Every decision on our technical roadmap is measured strictly by its net-positive environmental impact. Whether mapping global deforestation or segmenting critical biomass anomalies, we engineer exclusively for planetary preservation.

Ready to build?

Integrate our optimized deep learning architectures into your earth observation applications today.

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