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GoR AI-Powered Policy Navigator — l'assistant RAG du Rwanda pour l'accès aux politiques publiques

Rwanda · Kigali · Voir le profil de Rwanda · Voir le profil de Kigali

Preuves: Descriptif / auto-déclaré Top 67% 53/100 · Demandez à Evidence Copilot à propos de cette pratique

Créé par la RISA avec le NISR, l'AIMS Rwanda et Cenfri, le Policy Navigator rwandais répond sur les politiques publiques à partir de documents officiels vérifiés, et a été distingué parmi 59 des quelque 400 candidatures aux prix AI for Good 2026 de l'UIT.

50
Professionals trained in the DSCBI first cohort
24
Government institutions represented in the DSCBI cohort
1 of 59 (from ~400 submissions)
Recognition among global submissions at ITU AI for Good 2026
GoR AI-Powered Policy Navigator — l'assistant RAG du Rwanda pour l'accès aux politiques publiques

Détails

Maturité
Pilote
Promoteur
Rwanda Information Society Authority (RISA)
Période
2025-2026
Mots-clés
digital government, policy analysis, public administration

Contexte

Civil servants and citizens in Rwanda often struggle to locate the specific, current version of a policy, regulation or strategy among scattered government documents, slowing both compliance checks and public information requests. The Rwanda Information Society Authority (RISA), working with the National Institute of Statistics of Rwanda (NISR), the African Institute for Mathematical Sciences - Rwanda (AIMS Rwanda), Mastercard and Cenfri, built the 'GoR AI-Powered Policy Navigator'.

Objectifs

The tool uses retrieval-augmented generation (RAG) to answer multilingual queries about policies, regulations and strategies, drawing responses exclusively from verified government sources, and includes a secure workspace and an automated policy-alignment checker against national frameworks.

Activités

The Policy Navigator was built during the first cohort of the Data Science Capacity Building Initiative (DSCBI), a programme that trained 50 professionals from 24 government institutions, and was one of the top three projects from that cohort.

Résultats

The project was one of 59 projects, from nearly 400 global submissions, recognised at the ITU AI for Good Global Summit's Innovate for Impact 2026 awards, in the Open-Source AI for Global Impact category.

Conclusions

This is external, competitive validation of the concept, but neither RISA's announcement nor the award materials publish usage volumes, response-accuracy figures or a comparison of search time before and after; the efficiency claim that the tool 'significantly reduces time required to search through policy documents' remains self-reported.

Mise en œuvre
Coût indicatif
Faible (< 50 k€)
Délai jusqu’aux résultats
Court (< 1 an)
Personnel et compétences
Rwanda Information Society Authority (RISA), lead, National Institute of Statistics of Rwanda (NISR), African Institute for Mathematical Sciences - Rwanda (AIMS Rwanda), Mastercard, Cenfri

Conditions de réussite

  • Data Science Capacity Building Initiative (DSCBI) training 50 professionals from 24 institutions
  • RAG architecture restricted to verified government sources
  • Secure workspace and automated policy-alignment checker

Modes d’échec courants

  • No usage-volume, accuracy or before/after search-time figures published; the efficiency claim is self-reported

Habituellement financé par

National / regional programmes Philanthropic / foundation funding

Pistes de financement indicatives pour des pratiques de ce type — vérifiez toujours les appels en cours et les règles d'éligibilité de chaque programme.

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Sources de données

D'où proviennent les informations de cette pratique, et quand.

Pièces jointes

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