Climate resilience intelligence

The operating system for climate resilience.

Model climate baselines, simulate resilience pathways, and quantify the ROI of resilient future states.

Baseline

Exposure

Future

Intervention

Delta

ROI

Region: Cocoa supply region
Hazard: drought · heat · flood
Mode: ROI-ready decision layer
Illustrative model preview
04 / Investment case
LAT 06.42N · LON 03.88W1KM GRID

Avoided loss

$11.8M

ROI

3.4×

Payback

2.7 years

Yield-at-risk

24% → 11%

Resilience receipt

Avoided loss$11.8M
ROI3.4×
Payback period2.7 years
Supplier resilience58 → 81
Yield-at-risk24% → 11%

Problem

Resilience cannot scale without decision-grade metrics.

Resilience investments are increasingly becoming essential, but resilience practitioners struggle to compare baselines, quantify avoided loss, and translate physical risk into investment-ready evidence.

01 / Problem

No shared baseline

Projects are evaluated with bespoke benchmarks, making regions, assets, and portfolios hard to compare.

02 / Problem

ROI is fragmented

The benefits of resilience sit across finance, operations, communities, emissions, and avoided disruption.

03 / Problem

Capital needs evidence

Investors, insurers, and operators need quantified metrics before resilience investments can scale.

Model preview

Model the baseline. Simulate the intervention. Quantify the investment case.

Resilient measures today’s exposure against resilient future states, turning resilience pathways into metrics that teams can use to plan, finance, and report resilience projects.

01 / Map exposure

Map exposure.

Build one baseline for suppliers, crop risk, hazards, and vulnerable operating windows.

Region

Cocoa supply region

Yield-at-risk

24%

Exposure

$42M

Region: Cocoa supply region
Hazard: drought · heat · flood
Mode: Baseline climate exposure
Illustrative model preview
01 / Map exposure
LAT 06.42N · LON 03.88W1KM GRID

Yield-at-risk

24%

Supplier resilience

58 / 100

Financial exposure

$42M

ROI

Not modelled

Resilience receipt

Avoided loss$11.8M
ROI3.4×
Payback period2.7 years
Supplier resilience58 → 81
Yield-at-risk24% → 11%

02 / Test interventions

Test interventions.

Add drought-resistant seedlings, agroforestry, soil moisture, and flood buffers.

Seedlings

Drought-resistant

Land use

Agroforestry

Water

Soil moisture

Region: Cocoa supply region
Hazard: drought · heat · flood
Mode: Testing resilience pathways
Illustrative model preview
02 / Test interventions
LAT 06.42N · LON 03.88W1KM GRID

Interventions

4 pathways

Seedlings

Drought-resistant

Buffers

Flood + shade

Baseline

Locked

Resilience receipt

Avoided loss$11.8M
ROI3.4×
Payback period2.7 years
Supplier resilience58 → 81
Yield-at-risk24% → 11%

03 / Rerun the model

Rerun the model.

Compare baseline exposure against each resilient future pathway.

Yield-at-risk

11%

Exposure reduction

−38%

Supplier score

81 / 100

Region: Cocoa supply region
Hazard: drought · heat · flood
Mode: Resilient future state
Illustrative model preview
03 / Rerun the model
LAT 06.42N · LON 03.88W1KM GRID

Yield-at-risk

24% → 11%

Exposure

$42M → $26M

Supplier score

58 → 81

Avoided loss

Calculating

Resilience receipt

Avoided loss$11.8M
ROI3.4×
Payback period2.7 years
Supplier resilience58 → 81
Yield-at-risk24% → 11%

04 / Generate the case

Generate the investment case.

Turn the delta into avoided loss, ROI, payback, and reporting metrics.

Avoided loss

$11.8M

ROI

3.4×

Payback

2.7 years

Region: Cocoa supply region
Hazard: drought · heat · flood
Mode: ROI-ready decision layer
Illustrative model preview
04 / Generate the case
LAT 06.42N · LON 03.88W1KM GRID

Avoided loss

$11.8M

ROI

3.4×

Payback

2.7 years

Yield-at-risk

24% → 11%

Resilience receipt

Avoided loss$11.8M
ROI3.4×
Payback period2.7 years
Supplier resilience58 → 81
Yield-at-risk24% → 11%

Illustrative demo data. Not customer, investment, or underwriting advice.

Platform architecture

From physical risk to investment case.

Resilient connects spatial exposure, scenario modelling, economics, and reporting so teams can move from climate signal to capital decision.

01

Geospatial foundation

Assets, suppliers, hazards, intervention sites, and operating boundaries in one spatial model.

02

Scenario engine

Compare baseline exposure and resilient future states using consistent assumptions.

03

Spatial finance

Translate physical risk reduction into avoided loss, ROI, payback, and resilience metrics.

04

Reporting layer

Turn project performance into evidence for finance, operations, and regulatory reporting.

Why now

Modelling capability and physical-risk pressure are converging.

Geospatial AI is making resilience intelligence more granular and operational.

Physical risk is turning adaptation into a finance and supply-chain priority.

Teams need auditable metrics before resilience capital can scale.

Solutions

Solutions for resilience decision-makers.

Resilient supports the teams responsible for evaluating where resilience investments are needed, what interventions are worth funding, and how resilience performance can be measured.

Early access

Build the case for resilience investment.

Join the early practitioners shaping decision infrastructure for climate resilience.