dIAra — Costa Rica's Auditor Trains Cameras and a Neural Network on Public Construction Sites

Costa Rica's Contraloría General de la República (CGR), the country's supreme audit institution, built dIAra (Dispositivo de Inteligencia Artificial para Reconocimientos y Alertas) to monitor public construction projects in real time.

Deter irregularities, raise citizen trust, and give auditors earlier warning of problems on public-works sites.

The system pairs low-cost, solar-powered cameras — built from open-source designs and deployable on a MiFi connection — with a neural network trained on hundreds of site photographs to recognise construction machinery and people. Cameras capture images at intervals and upload them to the cloud, where the model estimates work/equipment activity and flags projects whose declared progress diverges from what the images show. The CGR published the camera hardware plans and AI models openly on GitHub, presented the project to peer Latin American audit institutions via an OLACEFS webinar, and submitted it to the Open Government Partnership's Open Gov Challenge.

As of 2025 the CGR had two complete mobile dIAra kits (two to three cameras, a MiFi router and a solar panel each), moved between sites, with a 2025 target of covering at least ten construction projects. A pilot at a school under construction was reported as completed with "very good results," though no quantified before/after figures on deviations caught or costs avoided have been published.

This is still an early-stage pilot — only two camera kits and a single fully reported deployment as of the latest public reporting — so its evidence of prevented corruption or cost savings is qualitative, not yet backed by published statistics.