We are building Africa's first foundational NLP architecture and dialect-rich data infrastructure. Moving beyond probabilistic attention to Dialectic Symbolic Transformers (DST).
Africa's linguistic landscape features over 2,000 languages with complex tonal and context-dependent structures.
Modern AI fails in Africa due to a lack of validated dialectic data and architectures capable of generalizing from small corpora.
Less than 5% of African languages are meaningfully represented in modern AI systems.
A crowdsourced pipeline ensuring 100% native-speaker verification, phonetic QA, and tonal integrity checks.
The Dialectic Symbolic Transformer (DST), a breakthrough in learning dialects from miniature datasets using deterministic reasoning.
Current Large Language Models (LLMs) rely on probabilistic methods requiring massive corpora, resources that do not exist for African dialects. LabelAfrica is pioneering the DST, a proprietary architecture optimized to learn African dialects from extremely small, curated datasets.
Built upon frontier progress on the Interaction Calculus, HVM4 and SupGen, inspired by Yves LaFont's Interaction Combinators computational model 1997.
Unlike traditional statistical models, the DST utilizes deterministic reasoning to map dialectic syntax. This allows for semantic accuracy and cultural nuance preservation without the need for billions of parameters.
To solve the "Low-Resource" problem fundamentally, creating a model that can be "plug-and-play" distilled into existing LLMs.
"We are engineering a breakthrough to learn dialects from small datasets, edging the world forward towards AGI via symbolic reasoning."
A gamified mobile experience for native speakers to contribute spoken and written data.
Users earn reward points while putting their native dialect on the digital map.
A social meeting application designed for tight-knit groups: Umunnas, Kindreds, Social Clubs, Age Grades, and Trade Unions.
Rooms are incentivized to speak in local dialects. Participants consent to follow-up labeling and transcription exercises during virtual coordination.
A tool for professional annotation, transcription, segmentation, and symbolic tagging.
All outputs undergo human native-speaker verification to ensure tonal and phonetic accuracy.
Target Audience: AI Labs, Governments, NGOs, and Global Enterprise.
Access the world's most linguistically diverse and verified dataset for African speech and multimodal AI.
Granular search by dialect, region, and tonal complexity.
Structured audit trails for reliability and dialect validation.
Breaking language barriers for aid and education distribution.
Enabling voice-first diagnostic tools for non-English speakers.
Competitive advantage in Language Localization and Adoption.
Start earning by speaking your mother tongue
Bring your Social Club or Union online.
Coordinate meetings and preserve your dialect.
We employ a remote network of trained labelers spanning multiple countries
Professional transcription, annotation, and QA. We provide training and weekly pay.
LabelAfrica.ai is Africa's first deep-tech lab focused on symbolic AI architectures.
We operate a physical office in Nigeria with 50 engineers and a remote network of 100+ trained labelers.
Tech Entrepreneur, and Author. Founder of ABIT Network and the Enugu Tech City initiative.
Software Engineer and AI researcher. Specialist in scalable applications and emerging tech solutions.
Still got questions you need clarifications on, Our
customer success team are excited to help you
