Generate purpose-built data
We can run a bespoke collection programme to create the speech, text, multimodal or human-feedback data required for a defined task.
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Goloka AI Data & Evaluation
Build and
evaluate AI with
the right people.
Goloka helps AI teams generate human data, work with relevant language and specialist communities, and evaluate how models perform for the people they are meant to serve.
How we can work with you
Start with the gap in your model or dataset.
You may already know the language, data type or evaluation task you need. Or you may simply know that your model is not performing well enough for a particular group of users.
We can start from either point.
Access existing data
Where appropriate datasets already exist and the rights allow commercial use, we can discuss suitable access or licensing arrangements.
Evaluate model performance
We can recruit relevant language speakers, users or domain specialists to test model outputs against defined criteria.
Build benchmarks
Where repeatable evaluation is needed, we can structure test sets and approaches to measure performance consistently over time.
How an AI data project works
You tell us what your model needs.
We build the human process around it.
We turn your model requirements into a structured human data and evaluation workflow, from task design and contributor qualification through collection, quality assurance and delivery.
Get Started with GolokaYou describe the requirement.
Share the model task, language, population, data modality, evaluation problem or performance gap.
We confirm the available supply.
We assess whether the relevant speakers, users or specialists can be recruited and what scale is realistic.
We design the task with you.
We agree on the contributor profile, task instructions, qualification process, consent requirements, quality controls and expected output.
We recruit and qualify the right people.
Participants are selected based on the requirements of the project rather than treated as a generic labour pool. For language projects, this can include language and dialect qualification. For specialist evaluation, it can include relevant professional or domain experience.
We collect and quality-assure the work.
We manage collection or evaluation workflow and apply the agreed review process before delivery.
You receive documented data or evaluation results.
The output is delivered with the agreed supporting information and quality controls.
What Goloka can generate
Different models require different
kinds of human input.
Language Speech & Text
Goloka can generate:Speech and conversational audio
Text generation and response data
Translation
Transcription
Image, Video & Multimodal Data
Goloka can generate:Image, Video & Multimodal Data
Multimodal datasets
Real-world observations used to ground or test AI systems
Feedback & Model Evaluation
Goloka can generate:Preference and ranking exercises
Human evaluation of model responses
Usability testing
Safety evaluation
Context & Specialist Evaluation
Goloka can generate:Language and cultural evaluation
Specialist or domain evaluation
Why Goloka
The people producing or evaluating the data should understand what it represents.
African data is not a single category.
Language changes by region and dialect. Cultural expectations vary. Agricultural questions require different knowledge from financial questions. A system that works well for one group of users may perform poorly for another.
We design the human side of AI data around this reality.
We recruit for context.
We identify participants according to the language, location, user group or specialist knowledge required by your task.
We can combine digital tasks with ground evidence.
Where the use case requires real-world observation, Goloka's field collection infrastructure can connect AI projects to evidence from actual communities, locations and operating environments.
We manage the workflow from recruitment through QA.
Our existing collection infrastructure supports participant coordination, tasking, quality assurance and payments.
We understand that rights matter.
The fact that data exists does not automatically mean it can be used to train or evaluate an AI system. We agree the intended use and required participant permissions as part of the project design.
Consent and data rights
Permission is part of the dataset.
Research participants, AI trainers, AI evaluators and commercial data contributors are not interchangeable. The work requires clear consent, use rights and handling rules.
We design sourcing and documentation around the intended use of the data so teams understand what they can use, how and under what conditions.
Read about data governance
Who we work with
Built for teams bringing AI into African contexts.
AI labs and model developers
African technology companies
AI data & evaluation companies
Enterprises deploying AI in Africa
Understand whether AI systems perform appropriately for employees, customers or other users in the markets where they will be deployed.
Development organisations
Evaluate language access, usability and performance for AI systems intended for public-interest or development use.
AI data is more than annotation.
We assess whether the relevant speakers, users or specialists can be recruited and what scale is realistic.
Get started Reach out to our team
What is difficult for
you to source or evaluate today?
Tell us the language, population, model type or data requirement. We will review the available supply and propose a realistic collection or evaluation approach.
Request Sample Data