Work

Deployed where
it matters.

We work with institutions that carry both the mandate and the urgency. We build live systems inside them, not reports about them.

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Deployment 001

Every deployment starts with a real problem inside a real institution. Not a pilot. Not a proof of concept. A working system, embedded in how decisions actually get made and designed to stay that way.

UNICEF's Centre of Excellence needed to move faster, think sharper, and justify every decision to donors, ministries, and programme teams simultaneously. We built the infrastructure to do that.

Case Brief Active
UNICEF
Global Centre of Excellence for Climate
Geography 6 Countries Pilot cohort, Phase 1
Engagement Climate Country Proposals Follow-on contract secured

Designing fundable, evidence-based proposals that translate climate risk into actionable programming across sectors and geographies — without rebuilding the entire analytical stack for each country.

Hotspot analysis at ADM3 resolution, a proprietary Intervention Attractiveness Index, and an impact-maximising budget model — synthesised through the Judgement Engine with full chain-of-thought traceability.

Faster to
proposal
Fewer revision
cycles
2.4×
More cost
efficient
By the numbers
Faster to proposal
6 countries in 6 months. The previous benchmark was 6 countries in 2 years.
Fewer revision cycles
An average of 2 iterations per report, versus the typical 4 to 5 with specialist consultants.
2.4×
More efficient on cost
$210k for 6 countries versus $500k, while delivering a higher ceiling on proposal quality.

The problem no one had solved

UNICEF's Centre of Excellence was sitting on some of the world's most rigorous climate data and still couldn't move from insight to action fast enough. Each Climate Country Proposal required a team of specialist consultants, $100 to $150k per country, and 24 months to cover six geographies.

The gap wasn't information. It wasn't expertise. It was the machinery to translate risk into operational decisions across sectors and geographies, without rebuilding from zero every single time.

The data existed. The decision-ready layer didn't.

Hotspot heatmap: hazard and vulnerability index
Hotspot heatmap: hazard × vulnerability index

What Verdera built

We decomposed the proposal process into its smallest working units — discrete lego blocks, each with a specified input and output, each independently executable. Three modules combined to cover the full scope of a Climate Country Proposal.

Hotspot Analysis mapped every climate hazard at ADM3 resolution, homogenised them into a single risk indicator, and layered in child vulnerability across health, education, sanitation, and livelihoods to produce a high-resolution risk map of every programme area in scope.

Intervention Assessment used a proprietary Attractiveness Index to rank every available intervention against the specific country context. Not a generic shortlist, but a ranked set calibrated to the risks and vulnerabilities already identified.

Budget and Impact Modelling allocated resources across interventions to maximise outcomes across multiple axes: direct and indirect beneficiaries, donor requirements, and sector-specific targets. Every number tied to its source.

Traceable reasoning. Every output tied to a source. Nothing generic.

Judgement Engine output: intervention ranking and budget allocation
Judgement Engine output: intervention ranking and budget allocation

Why it didn't end there

The follow-on contract wasn't a courtesy. It was the system working as designed. When you embed Verdera inside a client's workflow — not as a report delivered once, but as live infrastructure — the questions get more specific, the feedback loops get tighter, and the value compounds.

Three months into the pilot, UNICEF came back. The same lego blocks that powered the first six countries are now configured for the next cohort: faster, with a higher baseline, and with institutional memory that no consultant ever left behind.

Not a pilot. Not a report. A system that got more useful the longer it ran.

How we work

Every Verdera engagement follows the same four-stage sequence. The modules change. The rigour doesn't.

01

Scoping

We map the decision problem, not just the data gap. What needs to be decided, by whom, on what timeline, with what constraints — that shapes everything downstream.

02

Module selection

We select and configure the relevant components from our modular stack. Hazard context. Human vulnerability. Intervention database. No deployment uses all six — each is composed for the problem at hand.

03

Judgement Engine integration

The modules feed a domain-specific reasoning layer that synthesises outputs into decision-ready analysis. Every inference is traceable. Locally deployable where data sensitivity requires it.

04

Embedded delivery

We don't hand over a document. We embed the system as a dashboard, an agent, or a digital twin, directly into the client's workflow. Feedback loops are built in from day one. The system gets sharper with use.

Who works
with us

We work with institutions that carry the mandate to act on climate and need the operational infrastructure to do it at scale. Our deployments run inside intergovernmental bodies, bilateral donors, and national governments.

UN Agencies
UNICEF
Global Centre of Excellence for Climate
UNDP
Crisis Bureau, climate resilience
WFP
Anticipatory action programming
Bilateral Donors
KOICA
Korea International Cooperation Agency
GIZ
Climate and rural development
USAID
Resilience and food security
Governments
National DRR offices
Disaster risk reduction ministries
Planning ministries
Long-range climate investment planning
Health ministries
Climate-smart health system design
Research and Advisory
CGIAR centres
Food and agriculture systems
Policy institutes
Climate finance and adaptation strategy
Climate funds
Green Climate Fund, Adaptation Fund

Every institution we work with leaves with infrastructure, not a deliverable.

Systems that stay inside the workflow, compound value over time, and don't require rebuilding when the next problem arrives.

The adaptation gap isn't a data problem. It's an infrastructure problem. We're building the infrastructure.

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