Do you need a lot of data to do AI?

Not always. Many generative-AI use cases work on your existing documents. For machine learning, we first assess the quantity and quality of your data.

Is my data sent to third parties?

We favour architectures that keep your data under control: models hosted in controlled environments, pseudonymisation, appropriate contracts.

AI, Machine Learning & Agents | Africa Data Entry

Artificial intelligence only creates value when it solves a real problem, on reliable data.

We identify with you the use cases where AI creates measurable value: forecasting demand, detecting fraud, classifying documents automatically, assisting your teams with a conversational agent connected to your data.

Our data scientists build lean, explainable models trained on qualified data. Our AI engineers design agents that carry out complete tasks, with safeguards and human supervision.

We pay special attention to local languages, personal data protection and model frugality: useful AI doesn't need to be oversized.

−60%document-processing time
90 daysto a first use case in production
100%of assistant answers with sources

Our know-how

01
Machine learning
Forecasting, scoring, segmentation, anomaly detection, explainable models.
02
Generative AI & RAG
Assistants connected to your documents and databases, with cited sources.
03
AI agents
Automating complete tasks: extraction, checks, drafting, follow-ups.
04
MLOps & governance
Deployment, performance monitoring, bias, usage charter and compliance.