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K2G Enrichment

K2G Enrichment
Intelligent Data Enrichment Agent

Turn fragmented raw data into enriched, context-aware datasets powered by external sources, geodata, and automated integrations.

How it Works
Automated, smart, and context-aware enrichment process
K2G Enrichment automatically enhances your datasets with relevant external variables — from weather patterns to geolocation details — improving risk assessment and decision-making accuracy.
1
Automatically identifies enrichment opportunities

Analyzes your dataset and detects which external factors can strengthen your models

2
Connects external data sources

Weather data, geodata, government and commercial registries — all integrated seamlessly via Data Lake, API, or CSV pipelines

3
Geo-references and systematizes your data

Aligns records with geographic context, ensuring structured, enriched datasets ready for modelling and analytics

Typical challenges our clients face
When you need it
Typical challenges our clients face
Fragmented data lacking external context
Fragmented data lacking external context
Manual data merging leads to errors and wasted analyst time
Manual data merging leads to errors and wasted analyst time
Not enough variables to build accurate risk models
Not enough variables to build accurate risk models
The value you get
Enriched data = better decisions

With enriched datasets, insurers gain a fuller understanding of customer behavior, risk drivers, and portfolio exposure. External factors help uncover insights that raw internal data alone cannot reveal.

Array

More complete customer profiles

Additional data sources enhance risk models and support accurate segmentation

New factors for risk modelling

Weather, infrastructure, salary levels, local conditions — all available instantly

Faster data acquisition

Automation replaces manual data collection and reduces processing time

Ready to enrich your data?

See how K2G Enrichment transforms incomplete datasets into powerful analytical assets

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Key benefits
1
Lower Loss Ratio

Adding external variables (e.g., weather conditions) helps reduce portfolio losses — e.g., hail loss ratio decreased by 7% after enrichment

2
Better predictions and pricing strategies

Enhanced datasets result in more accurate forecasts and stronger tariff models

3
Automation and efficiency

No more manual data sourcing — the system handles integrations and updates automatically

4
Stronger portfolio insights

External context reveals hidden risks and correlations within your portfolio

Arina Man
Arina Man CEO K2G AG
info@k2g.ai
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    FAQ
    Do you have any questions?

    Everything you need to know about the product and billing. If you still can’t find the answer you’re looking for, just Contact us

    K2G integrates weather datasets, geolocation layers, infrastructure points, government and commercial registries, salary statistics, and third-party risk variables. Custom sources can be added upon request.

    No. You can integrate via API, upload CSV files, or connect your existing Data Lake — the system adapts to any workflow.

    External variables — such as weather patterns, road infrastructure, or demographic factors — significantly increase model accuracy and help uncover hidden correlations.

    Most clients see improvements within hours. Automated enrichment replaces weeks of manual data collection and reduces error rates immediately.