Trendify Labs
We research language models, culturally aware AI, connected knowledge and intelligent systems for African contexts and beyond.
Our work moves from understanding a problem, to building and evaluating models, to deploying systems that are useful in the world they serve.
Our research areas are applications of a broader question: how can intelligent systems understand language, people, knowledge and the contexts in which they operate?
Study the language, culture and social context a system is intended to serve, including the knowledge that standard datasets often miss.
Develop models and intelligent systems that can reason over relevant information, relationships and context.
Evaluate capability, limitations, safety and usefulness before models become products or workflows.
Investigate the language, problem or environment.
Develop models using relevant research and data.
Test reasoning, context, safety and limitations.
Integrate the work into useful Trendify systems.
Trendify Labs develops models for distinct kinds of intelligent work.
Our model work focuses on what systems understand, what they can reason over and how reliably they can serve their intended context.
Evaluation is part of the research process: we study performance, latency, limitations and safety rather than treating a model as finished when it can generate an answer.
Large language models can process and generate human language, but their performance varies across languages, cultures and communities.
An AI system can be linguistically fluent while misunderstanding the world in which a language is used. Our research treats that context as part of the model problem.
Our programmes connect model development with language, culture and community knowledge.
Research into how African linguistic, cultural and community knowledge can become part of the design, training, evaluation and deployment of intelligent systems.
The human and contextual layerRead the CA-AALLM paperThe model layer of our research programme, focused on building language intelligence for African contexts and developing models from the research around them.
Explore modelsCommunities are not passive sources of training data. Their language, knowledge and culture are part of the context intelligent systems must learn to respect.
Our commitmentsTAM is the model layer. Communities are the human and contextual layer. Together they frame the work required to build AI that is more useful for the people and environments it serves.
We apply the same AI research lens across domains where context, relationships and human judgment matter.
Cultural context is a fundamental component of meaning, not supplementary information.
Research into economic systems where informal activity, local markets and institutional variation matter.
Performance is shaped by tactics, opponents, competition, environment, history and human decision-making.
TSI (Trendify Sports Intelligence) is the football analysis studio this work feeds into, turning authorised match highlights into timestamped, evidence-linked observations.
Explore TSIAI must support institutions without removing human accountability from governance.
We study not only what models can do, but when they should be used and what limitations must be communicated.
We test harmful requests, privacy-sensitive requests, misinformation, prompt injection and adversarial prompts.
Our releases communicate benchmark conditions, limitations and the difference between internal results and broader validation.
Research involving communities must respect their knowledge, language and culture.
Trendify Labs
We work across language, culture, contextual AI, model development and intelligent systems. For research partnerships, community collaboration or technical enquiries, get in touch.