Services

Analytics

Leveraging the latest technology to build tools that reimagine development research and put insights within everyone’s reach.

Why Laterite?

In-house apps since 2021

We build custom, AI-powered apps with our dedicated team, tailored for the international development sector.

Better evidence, better decisions

Our tools turn complex data into interactive insights. From evidence to action, faster and with confidence.

Innovating for impact

We’re pioneers in AI for social impact, continuously investing in our capabilities to find new solutions to socio-economic development problems.

Knowledge management

One of the key challenges faced by decision-makers in the development sector is the difficulty in accessing a complete understanding of an evolving topic.

We’re testing new ways to use intelligent knowledge hubs, chatbots and dashboards to centralize and visualize curated information and metrics, to generate new insights for decision-making.

Operational efficiency

When carefully used, LLMs can be used to enhance internal processes and streamline routine tasks. Laterite can help your organization automate workflows and become more efficient.

We’re building custom applications to automate time and resource intensive tasks, including a suite of 20+ research efficiency apps called LateriteAI which are integrated into Slack.

End user apps student assessment option2

End-user applications

We build customized tools for use in the field by farmers, teachers or project implementers to improve their services.

For example, we’ve built AI-powered Whatsapp chatbots for rapid feedback on EdTech tools with teachers, and deployed optical recognition techniques that can be used to grade student assessments, monitor attendance sheets, or extract information from administrative data.

Geospatial insights

Social research is geographically situated. Laterite has a large database of geospatial data from the countries where we work. Indicators include, for example, terrain, climate, population composition and density, nightlights, distances from roads and urban centers, and a vegetation index.

We use geospatial statistics to strengthen econometric analysis and ground our findings in their geographical context. This allows us to enhance our analysis and build powerful maps & tools to visualize development-related indicators.

Predictive modeling

We use predictive analytics and modeling techniques to: define target populations, extract insights from unseen data, extrapolate findings, or plan ahead.

Some of the techniques we have used include: machine vision techniques to estimate coffee tree yields, Markov chain models to predict the evolution of education systems and gravity models to identify infrastructure gaps in Rwanda’s economic geography.