Climate Data Classification & Visualization

99.8% Accuracy

10x Faster analysis

Client Passifi Tech

Sector Climate tech

Confidentiality NDA protected

Climate Data Classification & Visualization

The challenge

Environmental data arrived in huge, varied volumes, and manual classification was too slow to keep pace with the questions researchers needed answered.

Our approach

We built automated pipelines that clean and classify large climate data sets with machine learning, then present the results in interactive visualisations.

The outcome

A climate intelligence platform that classifies environmental data accurately and turns weeks of analysis into fast, visual answers.

How we delivered

From problem to production

Four focused phases, each ending with something the client could see and test.

Data ingestion

Large environmental data sets collected and standardised.
Classification models

Machine learning models trained to label environmental patterns.
Visualisation

Interactive maps and charts for researchers and stakeholders.
Scale and tune

Pipelines optimised for speed as data volumes grew.

Highlights

What made the difference

The decisions and capabilities behind the results.

Classification Accuracy

Validated against ground-truth forestry and agronomy telemetry stations.

Query Velocity Increase

Complex temporal spatial analytics queries now execute in under 2 seconds.

Monthly Imagery Streamed

Autonomous cloud pipeline operating with zero manual intervention required.

Infrastructure Cost Efficiency

Cloud-Optimized GeoTIFF streaming cut expensive cloud egress storage bills.

Technology and standards Python TensorFlow PostgreSQL React Google Earth Engine

★★★★★

Pyzen Technologies provided us with a reliable web scraping and data automation solution for our business research needs. Their team understood the requirement clearly, managed the data extraction process professionally, and delivered accurate output on time.

Amit Verma Lead Researcher · Passifi Tech

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