Fintech · Insurtech · 200–1000 · Europe #b010_14

Context

We underwrite parametric cover for weather and climate risks, using satellite and sensor data to trigger fast payouts for corporate and public clients.

Industry

Fintech · Insurtech

Size

200–1000 employees

Region

Europe

Tools budget

$5K–20K per month

Needs

Data pipelines & integration. We ingest large external climate and satellite datasets, and our orchestration struggles as sources multiply.

Today: scientific engineers run climate-model data jobs on containers with orchestration · Urgency: this year

Data quality & observability. A silent gap in an external data feed can distort a payout trigger, so we need automatic checks.

Today: scientists validate model inputs through code checks and peer review · Urgency: this year

Cloud cost optimization. Geospatial processing drives cloud spend up and we lack visibility into which workloads cost most.

Today: engineers manually track cloud spend while benchmarking compute for models · Urgency: this year

Who decides

head of data · team trial

Expects from suppliers

Strong support for geospatial and time-series data; Works with our existing cloud warehouse; Alerting on data freshness

Not a fit

Tools limited to tabular business data; On-premise only products

Stack

cloud: GCP-class hyperscaler, Kubernetes, data warehouse: cloud

Buying triggers

scaling transaction volume, cost pressure