For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
W
Wakmate Ai

Wakmate Ai

Agency
Kenya flagNairobi, Kenya
www.wakmate.com
$30.00/hrIntermediate167+

Key Skills

Software

CVATCVAT
Other
LabelboxLabelbox
V7 LabsV7 Labs
Internal/Proprietary Tooling
ArgillaArgilla
DatatureDatature
RoboflowRoboflow

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
TextText
VideoVideo

Top Task Types

RLHFRLHF
Evaluation/RatingEvaluation/Rating
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
SegmentationSegmentation
Object DetectionObject Detection

Company Overview

Wakbod Limited is a tech startup incorporated in Kenya in April 2024 and operates three brands, among them Wakmate AI, which specializes in Data Labelling & Annotation, RLHF, and Expert Sourcing. Wakmate AI comprises an elite technical team of 167 STEM-vetted associates with extensive expertise in Mathematical Logic, Physics, Engineering, Cybersecurity, Chemistry, Biology, among other technical and non-technical subjects. Our core competency is bridging the gap between raw data and "Scientific Ground Truth," with specialization in RLHF and high-fidelity Computer Vision for frontier AI models. We have architected secure data pipelines for complex 3D LiDAR fusion, Chain-of-Thought logical verification, and differential privacy implementation. Through the application of rigorous Inter-Annotator Agreement (IAA) protocols, we have successfully delivered high-stakes datasets where sub-centimeter precision and logical consistency were much-needed. We are seeking to integrate our high-cognitive technical layer with a platform that values data integrity as a competitive advantage. Our goal is to provide the specialized oversight and vetted talent that is necessary to tackle "Level 5" AI challenges, which require deep subject matter expertise that traditional high-volume crowdsourcing cannot reliably provide. We also have a labelling and annotation tool integrated into our platform, which allows us to assign only one task at a time to our annotators and experts on their working dashboard, which boosts data security. This also allows us to import data directly into our platform through APIs and webhooks. We have three levels of quality review where all completed tasks go to QAs, then move to Lead QAs, and finally to the Approvals team for final review and approval before being sent to clients. As an additional data protection measure, we sign NDAs with all our annotators, experts, reviewers, and all our staff, which adds an extra layer to our measures aimed at protecting our clients' project data. We have worked on more than 30 projects so far, and we always aim at attaining 98%+ quality level and maintain clients' data privacy. We have always achieved this goal.

IntermediateEnglish

Security

Security Overview

Our company has adequate security measures in place to protect our staff and assets. The building in which our offices are located has security guards, with 24-hour surveillance of the premises using CCTV cameras, as it is used 24/7 with different shifts. Access to the builing is restricted. In our office, we restrict access to only our staff and annotators/experts. This is to protect the data that may be on our computers' screens at any given moment. Additionally, all our computers in the office have antivirus installed in them, and this is also a strict requirement for all our staff and annotators/experts who would like to use their personal computers. Our internet is strictly for internal use by our staff and annotators/experts in the office, and it is against our policy for them to share any internet passwords with unauthorised individuals. These are meant to prevent unauthorised access to our office computers via the wifi network. Additionally, we sign NDAs with all our staff, annotators/experts to prevent any of our clients' information or project details from being shared with third parties. We also conduct regular checks and scans on our computers as well as private staff and annotator/expert computers to ensure that no malware exists on them. We also regularly train our staff and annotators/experts on how to protect their computers while using the internet.

Labeling Experience

Labelbox

Autonomous Vehicle Object Detection Dataset Annotation

LabelboxVideoSegmentationPoint Key Point
Annotated street-level image and video datasets for autonomous driving AI systems. Tasks included segmentation of road objects and keypoint labeling for pedestrians and vehicles across video frames.

Annotated street-level image and video datasets for autonomous driving AI systems. Tasks included segmentation of road objects and keypoint labeling for pedestrians and vehicles across video frames.

2025 - 2026
Argilla

AI Code Generation Evaluation and Ranking Project

ArgillaTextEvaluation RatingQuestion Answering
Evaluated AI-generated programming outputs for correctness, efficiency, and logical structure. Ranked multiple model-generated solutions and provided feedback to improve code generation quality.

Evaluated AI-generated programming outputs for correctness, efficiency, and logical structure. Ranked multiple model-generated solutions and provided feedback to improve code generation quality.

2025 - 2025
Argilla

AI Model Red Teaming and Safety Evaluation Project

ArgillaTextRed TeamingEvaluation Rating
Conducted adversarial testing of AI models to identify unsafe, biased, or incorrect outputs. Evaluated model responses under edge-case prompts and provided structured feedback to improve safety alignment.

Conducted adversarial testing of AI models to identify unsafe, biased, or incorrect outputs. Evaluated model responses under edge-case prompts and provided structured feedback to improve safety alignment.

2025 - 2025

Search Relevance and Product Classification for E-commerce AI

Internal Proprietary ToolingTextClassificationEvaluation Rating
Evaluated search query relevance and product matching outputs for recommendation systems. Classified product listings and ranked AI-generated search results based on relevance.

Evaluated search query relevance and product matching outputs for recommendation systems. Classified product listings and ranked AI-generated search results based on relevance.

2025 - 2025

Financial Transaction Classification and Fraud Detection Labeling

Internal Proprietary ToolingTextClassificationEvaluation Rating
Worked on labeling financial transaction data for fraud detection models. Tasks included classification of transaction types, identifying anomalies, and evaluating AI-generated fraud risk predictions.

Worked on labeling financial transaction data for fraud detection models. Tasks included classification of transaction types, identifying anomalies, and evaluating AI-generated fraud risk predictions.

2025 - 2025