What challenges did Tardigrade AI face before AI implementation?

Handling increasing computing needs and infrastructure management with legacy hosting. Need to scale climate risk model computing flexibly while ensuring GDPR compliance. Transforming highly complex scientific climate data into actionable insights accessible by non-specialist clients.

What was the impact of the AI solution?

Automated reporting, reducing manual effort and improving client understanding of climate risk. Highly scalable, GDPR-compliant infrastructure supporting diverse data sources and complex analytics. Enables clients to make informed decisions with clear, operational climate risk indicators down to location level. Accelerated development and international expansion supported by Google Cloud innovation strength.

Source

GCP

Tardigrade AI transforms climate risk analytics with Google Cloud

Use case typeFraud detectionUpdated Jun 13, 2026

Tardigrade AI enables organizations to anticipate their exposure to climate hazards by transforming complex scientific data into precise financial risk indicators. The company migrated from university supercomputer hosting to Google Cloud for a scalable, flexible platform using BigQuery, Cloud Run, Cloud SQL, Cloud Storage, Cloud Workflows, and Pub/Sub. Gemini AI models interpret complex climate and econometric data into accessible language, generating automated client reports with actionable insights and recommendations. The platform scales dynamically with Cloud Run to control costs and handle varying workloads, while ensuring GDPR compliance. Future developments include natural language querying of BigQuery with Gemini and integration with tools like Looker and Google Earth for dynamic visualization.

Organization: Tardigrade AI
Industry: Finance
Location: France

Reported outcomes

Strategic outcomes

New product / capabilityAutomated client climate risk reportingRisk & complianceGDPR-compliant scalable infrastructureBetter decisions & insightActionable climate risk indicatorsMarket & geographic expansionSupported international expansion

Primary read

Use case focus

Showing 3 of 3

1Climate Risk Analytics
2Generative AI
3Data Analytics

Handling increasing computing needs and infrastructure management with legacy hosting.
Need to scale climate risk model computing flexibly while ensuring GDPR compliance.
Transforming highly complex scientific climate data into actionable insights accessible by non-specialist clients.

Migrated to Google Cloud with a cloud-native architecture rebuilt alongside Valtech.
Implemented BigQuery for unified data access from heterogeneous sources and used managed services for operational simplicity.
Integrated Gemini generative AI models to translate model outputs into natural language summaries and actionable client reports.
Utilized Cloud Run for on-demand scalability, Cloud SQL and Storage for data management, and Cloud Workflows and Pub/Sub for orchestration.

Technologies

BigQuery Cloud Run Cloud SQL Cloud Storage Cloud Workflows Pub/Sub Gemini

Automated reporting, reducing manual effort and improving client understanding of climate risk.
Highly scalable, GDPR-compliant infrastructure supporting diverse data sources and complex analytics.
Enables clients to make informed decisions with clear, operational climate risk indicators down to location level.
Accelerated development and international expansion supported by Google Cloud innovation strength.

Architecture

Cloud-native architecture with BigQuery, Cloud Run, Cloud SQL, Cloud Storage, Cloud Workflows, and Pub/Sub. Gemini AI models used for natural language interpretation of complex climate and econometric data.

Implementation partners1

Valtech

Sources & evidence1

Groundedness: 4/5

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

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Customer evidence