Our work.

A lightweight, offline-first data collection and synchronization platform built for field research in low-connectivity environments. Powers surveys, geospatial data gathering, and real-time sync when connectivity is available.

An offline-capable point-of-sale and inventory management system designed for African retail businesses. Works without internet, syncs seamlessly when connected.

An open research specification and benchmark for evaluating how AI models understand African languages, contexts, and cultural nuances. Driving better representation in foundation models.

Enterprise-grade platform for adapting foundation models (Google, Meta, Cohere) to specific business domains using supervised fine-tuning and RLHF. Includes automated evaluation pipelines.

A comprehensive data pipeline that integrates enterprise data sources into the fold of foundation models. Handles cleaning, transformation, embedding, and secure storage.

Open-source SDK for building applications that work entirely offline, with automatic conflict resolution and synchronization when connectivity is restored. Python and TypeScript support.

Curated multilingual dataset covering 50+ African languages, designed for training and evaluating NLP models on African linguistic contexts.

Intelligent routing layer that selects the optimal foundation model for each request based on cost, latency, accuracy, and domain specificity requirements.