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Earth's AI Intelligence Platform

Replace analyst teams with AI agents

Agents write, test, and run geospatial code to deliver decision-ready outputs across any domain tied to the physical world.

Financial Analysis

Port Activity

Port Activity

Infrastructure Investment

Infrastructure Investment

Commodity Tracking

Commodity Tracking

Geopolitical Analysis

Border Activity

Border Activity

Refugee Movement

Refugee Movement

Maritime Claims

Maritime Claims

Agriculture Monitoring

Crop Health

Crop Health

Irrigation Analysis

Irrigation Analysis

Harvest Planning

Harvest Planning

See Klarety in Action

Built to make you extraordinarily productive, Klarety is the best way to do analysis with AI.

Experience Klarety's advanced geospatial intelligence platform through this interactive video demonstration. Discover how our AI-powered system seamlessly integrates satellite imagery, natural language processing, and machine learning to deliver real-time geospatial insights and automated analysis at global scale.

Built for Intelligence at Scale

Every angle. Every source. Klarety pulls analysis from every domain to give you the full picture, backed by sources. While you focus on decisions.

Best-in-Class Infrastructure

Powered by Claude (Anthropic) for agent intelligence, Google Earth Engine for geospatial compute, and xAI for enhanced model capabilities and real-time public information retrieval.

Explore capabilities
Infrastructure
Connected
AI
Claude
Agent Intelligence
GEE
Google Earth Engine
MODISLandsatSentinel-1Sentinel-2
xAI
Grok
Real-time Data

Agentic Workflow & Code Executor

Execute complex intelligence and geospatial analyses through natural language. Our AI agents write, test, and run code autonomously to deliver actionable insights.

Learn about agents
crop_analysis.py
Running
1import ee
2from klarety import Agent, Task
3
4# Initialize geospatial agent
5agent = Agent("crop-analysis")
6region = ee.Geometry.Rectangle(
7 [-93.2, 41.5, -92.8, 41.9])
8
9# Fetch Sentinel-2 imagery
10imagery = agent.get_imagery(
11 source="SENTINEL-2",
12 date_range=("2026-01", "2026-01")
13)
14
15# Compute NDVI and yield forecast
16ndvi = agent.compute_ndvi(imagery)
17forecast = agent.predict_yield(ndvi)
18
19print(f"Yield: {forecast} bu/acre")

Event-Driven Automation

Set up trigger, event, or geo-fenced based automation with AI Agents. Monitor regions and receive intelligent alerts when changes occur.

Explore automation
Agents·Agricultural Analysis
Live
Farm Selected
Iowa Corn Belt · 2,400 ha
✓
NDVI Analysis
-8.3% vs last month
✓
Yield Forecast
↓ 12% · drought risk
✓
Hedge Signalprocessing
Long CORN Dec '26 @ $4.82