MLI-003

Ignitia Climate Advisory (SMS weather advice for smallholders).

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Mali Sub-Saharan Africa Low income Operational Deployment (Limited Rollout) Confirmed

World Food Programme (WFP) Mali; Ignitia AB (service provider).

At a Glance

What it does Prediction (including forecasting) — Trend and shock forecasting
Who runs it World Food Programme (WFP) Mali; Ignitia AB (service provider).
Programme Ignitia Climate Advisory (SMS weather advice for smallholders).
Confidence Confirmed
Deployment Status Operational Deployment (Limited Rollout)
Key Risks Not assessed
Key Outcomes With WFP in Mali, 5,481 farmers received weather updates/advice; reported ~10% yield improvement (programme-reported).
Source Quality 3 sources — News article / media, Report (multilateral / development partner)

Ignitia is an external startup and social enterprise supported by the World Food Programme (WFP) Innovation Accelerator that has developed a unique weather forecasting model to serve smallholder farmers across sub-Saharan Africa. Founded in 2010 by a research team drawn from universities and research institutions including NASA, Ignitia spent four years developing its proprietary forecasting technology. The system uses an advanced physics and Artificial Intelligence (AI) predictive model to deliver highly accurate, localized weather predictions and climate-smart agricultural advice to farmers. The core problem Ignitia addresses is the unreliability of conventional weather forecasts in sub-Saharan Africa, where more than 96 percent of cultivated land is rain-fed and changing rainfall patterns due to climate change represent a significant concern. Weather accounts for up to 80 percent of the yield gap experienced among farmers, making reliable weather information crucial for better yields, reduced costs and risks, and climate resilience.

Technically, the forecasting system — branded as iska — combines proprietary algorithms, uninterrupted three-dimensional multisource data, and predictive artificial intelligence developed by a team of meteorologists, physicists, and mathematicians. Ignitia has modelled physics suited for meso scales with new parameterisation schemes and ensemble methodology, tailored for tropical conditions with different data assimilation and initialization techniques. The model does not require ground weather stations, relying instead on geospatial and remote sensing data. The iska system generates GPS-specific two-day, monthly, and seasonal forecasts, which have proven to be 84 percent accurate in West Africa compared with 39 percent accuracy achieved by global forecasts such as those available from major international broadcasters.

The service delivers forecasts to farmers via SMS in a text-lite format that can be received on any basic mobile phone. The SMS message design was refined through 120 trials, resulting in an intuitive seven-keyword format that can be comprehended even by populations with low literacy levels. Each forecast is tailored to the specific farmer's location through an automated application that fetches the most common GPS coordinate for each subscriber. Farmers receive daily text messages on rainfall forecasts or weekly climate-smart agricultural advice tied to their location and crop. An app also allows access to richer weather risk content for subscribers such as field agents. The service is delivered in partnership with mobile network operators and other partners along the agricultural supply chain.

In the context of Mali, the WFP partnered with Ignitia to deliver hyper-local rainfall and forecast advice via SMS to smallholder farmers. Together with WFP in Mali, 5,481 smallholder farmers received critical weather updates and advice from Ignitia, with reported improvements in resilience and yields of about 10 percent. The messages delivered to farmers are advisory in nature, with final decisions on agricultural activities remaining with the farmers themselves.

Globally, Ignitia operates across 11 countries — including Benin, Burkina Faso, Ivory Coast, Ghana, Mali, Nigeria, Senegal, and Togo — and has provided services to 2.7 million smallholder farmers to date, of which approximately 700,000 are recurrent users. According to a 2021 study conducted with a sample group in Ghana, 92 percent of users receiving iska SMS rainfall messages experienced yield increases, 91 percent experienced income increases, and two out of three male farmers changed to better agricultural practices. In 2024, Ignitia's collaboration with WFP expanded to Ghana, where the venture signed a Long-Term Agreement with WFP Ghana for the next three years. The WFP Innovation Accelerator, based in Munich, Germany, provides support to Ignitia as part of its portfolio of innovation ventures. Ignitia's partners and investors include Novastar, IKEA Social Entrepreneurship, HACK VC, FINCA Ventures, Norrsken Foundation, and others.

The Ignitia team includes a Regional Director for Africa based at Ignitia AB, partnerships and business development staff at Ignitia, and an Innovation Ventures Project Lead at the WFP Innovation Accelerator who oversees the collaboration.

Classifications follow the DCI AI Hub Taxonomy. Hover over field labels for definitions.

Social Protection Functions

Implementation/delivery chain
Provision of payments/services primary
SP Pillar (Primary) The social protection branch: social assistance, social insurance, or labour market programmes. Social assistance
Programme Name Ignitia Climate Advisory (SMS weather advice for smallholders).
Programme Type The type of social protection programme, classified under social assistance, social insurance, or labour market programmes. View in glossary Other
System Level Where in the social protection system the AI is applied: policy level, programme design, or implementation/delivery chain. View in glossary Implementation/delivery chain
Programme Description WFP Mali partners with Ignitia AB to deliver hyper-local weather forecasts and climate-smart agricultural advice via SMS to smallholder farmers, enabling them to make better-informed decisions about agricultural activities to improve yields and climate resilience.
Implementation Type How the AI output is produced: Classical ML, Deep learning, Foundation model, or Hybrid. Affects validation, compute requirements, and governance profile. View in glossary Classical ML
Lifecycle Stage Current stage in the AI lifecycle, from problem identification through to monitoring, maintenance and decommissioning. View in glossary Monitoring, Maintenance and Decommissioning
Model Provenance Origin of the AI model: developed in-house, adapted from open-source, commercial/proprietary, or accessed via third-party API. View in glossary Commercial/proprietary
Compute Environment Where the AI system runs: on-premise, government cloud, commercial cloud, or edge/device. View in glossary Not documented
Sovereignty Quadrant Classification of data and compute sovereignty: I (Sovereign), II (Federated/Hybrid), III (Cloud with safeguards), or IV (Shared Innovation Zone). View in glossary Not assessed
Data Residency Where the data used by the AI system is stored: domestic, regional, or international. View in glossary Not documented
Cross-Border Transfer Whether data crosses national borders, and if so, whether documented safeguards are in place. View in glossary Not documented
Decision Criticality The rights impact of the decision the AI supports. High criticality requires HITL oversight; moderate requires HOTL; low may operate HOOTL. View in glossary Low
Human Oversight Type Level of human involvement: Human-in-the-Loop (active review), Human-on-the-Loop (monitoring), or Human-out-of-the-Loop (periodic audit). View in glossary HOOTL
Development Process Whether the AI system was developed fully in-house, through a mix of in-house and third-party, or fully by an external provider. View in glossary Mix of in-house and third-party
Highest Risk Category The most significant structural risk source identified: data, model, operational, governance, or market/sovereignty risks. View in glossary Not assessed
Risk Assessment Status Whether a formal risk assessment, informal assessment, or independent audit has been conducted for this system. Not assessed

Impact Dimensions

Equality, non-discrimination, fairness and inclusion
Systemic and societal
CategorySensitivityCross-System LinkageAvailabilityKey Constraints
Geospatial and remote sensing dataNon-personalSingle source (no linkage)Currently available and usedProprietary physics-informed and AI predictive model tailored for tropical conditions; does not require ground weather stations
Telecommunications and mobile dataPersonalSingle source (no linkage)Currently available and usedFarmer phone numbers and GPS coordinates used for SMS delivery; minimal personal data collected

UNDP (2015). Using SMS texts to provide weather forecasts for small farmers in West Africa. ReliefWeb. Available at: https://reliefweb.int/report/world/using-sms-texts-provide-weather-forecasts-small-farmers-west-africa (Accessed 23 Mar 2026).

View source News article / media

United Nations Development Programme (UNDP) (n.d.). Digital X Solution: Ignitia. UNDP Digital X. Available at: https://digitalx.undp.org/catalogs/ignitia.html (Accessed 23 Mar 2026).

View source Report (multilateral / development partner)

WFP Innovation (2025). Ignitia. Munich: World Food Programme Innovation Accelerator. Available at: https://innovation.wfp.org/project/ignitia (Accessed 31 Oct 2025).

View source Report (multilateral / development partner)
Deployment Status How far the system has progressed into real-world operational use, from concept/exploration through to scaled and institutionalised. View in glossary Operational Deployment (Limited Rollout)
Year Initiated The year the AI system was first initiated or development began. 2010
Scale / Coverage The scale and geographic or population coverage of the deployment. 5,481 smallholder farmers in Mali; 2.7 million farmers across 11 countries globally
Funding Source The source(s) of funding for the AI system development and deployment. WFP Innovation Accelerator
Technical Partners External technology vendors, academic partners, or development partners involved. Ignitia AB (Ignitia SMS advisory service).
Outcomes / Results With WFP in Mali, 5,481 farmers received weather updates/advice; reported ~10% yield improvement (programme-reported).

How to Cite

DCI AI Hub (2026). 'Ignitia Climate Advisory (SMS weather advice for smallholders).', AI Hub AI Tracker, case MLI-003. Digital Convergence Initiative. Available at: https://socialprotectionai.org/use-case/MLI-003 [Accessed: 1 April 2026].

Change History

Created 30 Mar 2026, 08:40
by v2-import (import)