8 out of 10 AI projects fail due to lack of accurate training data. Our team of domain experts work with different data types across a wide range of industries from data creation to clean-up, classification and labeling. In partnership with Izwe.ai, we also offer transcription and translation across the various African languages. We aim to produce unbiased and inclusive representation of datasets to feed factual information for machine learning models.
We use secure cloud environments and we have the ability to provide technical data pipeline support to clients.
End to end platform to work on your data and train your machine learning model.
Upload your data.
Import data (Cloud).
Ingest (API Endpoint + mapping-wrapper)
Select ML for auto label
Upload ground truth
Auto-label using your model, our models, or call on HitL
Compare ground truth
Visualize taxononomy distribution
QA randomize samples
Raise common errors & corrections
Run benchmark (generate sample, multi-parameter)
Train ML model
Download annotations / ML + formats
Export to cloud platform
Host ML model (API)
Deliver annotations to API
A dedicated Project Manager will work with you to understand your needs and source the right skill sets that have insights into your industry to accurately and efficiently produce the output.
We pride ourselves in our best-in-class domain experts but should the quality and accuracy of the datasets not meet your standards that we will redo the work at no additional charge to you.
We use secure cloud environments with dedicated resources for each individual client. A secure data pipeline is in place that allows us to read and label data directly from our clients’ cloud storage environments without having to ever download the data to our platforms.
Data privacy, security and compliance is our number 1 priority. We understand the sensitive nature of the datasets we work with and therefore we treat our clients’ data with the respect it deserves. All our platforms and tools are built in secure cloud environments with dedicated resources for each individual client.
We continue to invest in our underlying architecture and have developed a secure data pipeline to process data between us and our clients. This allows us to read and label data directly from our clients’ cloud storage environments without having to ever download the data to our platforms.
Together with the technological interventions we have implemented we also have strict NDAs with our workforce of labelers to further ensure we treat our clients’ data confidentially.
See more information on our privacy policies here: