The talent behind better AI
Human expertise for better AI.
We connect AI companies with vetted experts in the fields their models need, so they can build high-quality training data, evaluate models, and test AI agents.
Solutions
Services built around specific evaluation needs.
Every engagement is matched to people who know the subject, whether that means reading code or judging practice in a professional field.
LLM Evaluation
Structured human assessment of language model responses.
- Accuracy
- Relevance
- Instruction following
- Reasoning
- Safety
- Response quality
Coding Evaluation
Working engineers review model-generated code and reasoning.
- Generated code
- Debugging
- Code quality
- Correctness
- Software engineering reasoning
AI-Agent Evaluation
Experts test AI agents on realistic workflows.
- Task completion
- Tool use
- Reasoning
- Reliability
- Instruction following
- Failure modes
Training Data
Human experts generate material models can learn from.
- Prompts
- Responses
- Preference pairs
- Explanations
- Corrections
- Domain-specific examples
Domain Expert Evaluation
Evaluation that needs professional or academic judgement rather than code.
- Factual correctness in a specialist field
- Soundness of reasoning
- Appropriate caution and caveats
- Terminology and conventions
- Where an answer would mislead a non-expert
Arabic & MENA Evaluation
An emerging specialisation in Arabic and regional AI evaluation.
- Arabic LLM evaluation
- Dialect evaluation
- Cultural relevance
- Translation
- Safety
- Instruction following
How it works
Four steps from requirement to validated data.
We design a dedicated pipeline for every task, from the first specification through execution and quality control to final delivery.
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01
Define
You tell us what needs to be evaluated or generated.
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02
Match the talent
We select qualified experts based on subject-matter expertise, technical skills, language, experience, and qualification results.
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03
Execute & QA
Experts complete the work. Outputs go through quality-control procedures.
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04
Deliver
You receive structured, validated results and data.
- Client need
- Expert selection
- Human work
- Quality assurance
- Validated data
Why us
Talent that is hard to find.
Our background gives us direct access to a strong pool of specialists, including Arabic speakers, who are difficult to reach through general talent channels.
Vetted expertise
Experts are assessed before they join the Talenor Network.
Subject-matter depth
We match the expertise to the work, whether that means reading code or judging practice in a professional field.
Human and automated QA
We use human review and automated checks where appropriate.
Flexible capacity
Projects can scale from small pilots to larger workloads.
Specialised evaluation
We build domain-specific evaluator pools rather than treating every task as generic annotation.
How experts are selected
The full screening and qualification process is written out in detail.
About
Building the human layer for AI systems.
AI systems are increasingly limited less by model architecture than by the quality of the human judgement used to train and evaluate them. Careful evaluation, well-constructed training examples, and honest assessment of where a system fails all require people with real domain expertise.
Talenor exists because the hardest part is rarely the work itself. It is finding the right person to do it. We are building the Talenor Network, a specialised pool of experts, together with the operational process required to apply their judgement to AI evaluation and data work reliably. Some of that work is technical. Much of it is not: a model can be judged only by someone who knows the subject well enough to tell a right answer from a plausible one.
We are an early-stage company. Rather than describe a track record we do not yet have, we would rather be precise about how we work: how experts are qualified, how work is checked, and what a client actually receives at the end of a project.
The right expert, not the nearest one
Work is matched to people who know the subject, rather than to whoever is available.
Specialisation over volume
We build domain-specific evaluator pools rather than treating every task as generic annotation.
Quality control is part of the work
Human review and automated checks are built into the process, not offered as an upgrade.
Say only what is true
We do not publish customer names, statistics, or case studies we cannot substantiate.
Working with us
Start small.
Most engagements begin as a small pilot: a defined batch of tasks with an agreed specification and quality bar. A pilot tells both sides what they need to know: whether the expert pool matches your domain, whether the specification survives contact with real data, and what throughput is realistic.
From there, the same workflow scales to larger or ongoing work. If a pilot shows we are not the right fit for your problem, we will tell you.
For experts
Want to help build better AI?
Join the Talenor Network: engineers and researchers, and experts in their own professional and academic fields. Qualified experts may receive opportunities to work on AI training and evaluation projects.
Have an AI evaluation or data project?
Tell us what you need. We'll help define the workflow and identify the expertise required.