Task-level expertise
Identify the specific work an AI system needs to perform, from clinical reasoning to financial analysis to contract review.

Human knowledge. Model progress.
Alpheva builds specialized expert networks across professions and specialist fields.
We turn real-world judgment into training data, environments, and evaluations.
Expertise is more than a domain
A domain is only the starting point.
The right expert depends on the task your model needs to perform, the skills and tools involved, and the standard of a good outcome.
Alpheva maps AI workloads to the precise expertise required to perform and evaluate them.
Finance
Investment Management
Equity Research
Institutional-quality investment analysis
From broad domains to the precise expertise required for real-world work.
Expertise taxonomy
Our taxonomy connects professional domains to the specific specialties, tasks, skills, tools, and judgment required for real-world work.
It lets us move from:
What does the model need to do?
What expertise is required to do it well?
Which experts can perform and evaluate that work?
and move to:
Identify the specific work an AI system needs to perform, from clinical reasoning to financial analysis to contract review.
Define the specialty, experience, skills, tools, and judgment required for each task.
Capture not just what an expert does, but what good performance looks like.
Expertise coverage
From established professions to specialized crafts, every discipline brings its own way of thinking.
Experts review financial models, check accounting and tax assumptions, and evaluate insurance, investment, and risk analyses.
Practitioners review business strategies, evaluate product and marketing decisions, and assess management, HR, and project workflows.
Engineers check design calculations, review manufacturing procedures, and test model outputs against physical and engineering constraints.
Practitioners test purchasing and fulfillment workflows, review operational decisions, and evaluate how AI agents handle real-world business processes.
Experts evaluate reasoning, behavior, human decision-making, user interactions, and AI outputs involving cognitive and behavioral judgment.
Specialists review policy analysis, evaluate public-sector workflows, and assess evidence, regulatory context, and public-service outcomes.
Practitioners review code, test security scenarios, and evaluate how AI systems use software, data, and technical tools.
Specialists review clinical reasoning, assess research and medical content, and evaluate outputs against professional standards.
Specialists evaluate agricultural recommendations, review production scenarios, and assess assumptions against real-world growing and operating conditions.
Practitioners review building plans, evaluate project estimates, and assess construction, infrastructure, and real-estate workflows.
Language specialists evaluate meaning, fluency, cultural context, terminology, translation quality, and communication across languages and domains.
Educators review instructional content, design assessments, evaluate tutoring responses, and assess learning outcomes against educational standards.
Specialists review legal analysis, assess contract language and supporting evidence, and evaluate legal research and compliance workflows.
Researchers create scientific problems, verify calculations, assess experimental reasoning, and evaluate whether conclusions follow from evidence.
Experts interpret geological and resource data, review operational decisions, and evaluate technical outputs against industry constraints.
Practitioners verify historical and cultural context, review creative work against a brief, and evaluate accuracy and interpretation.
Specialists review aerospace and aviation systems, assess intelligence analysis, and evaluate defense and security workflows against operational requirements.
Specialists identify, classify, evaluate, and explain highly specific knowledge that is rarely represented in conventional datasets.
From AI workload to expert data
Every AI system has different requirements.
We translate those requirements into precise expert workflows and turn the resulting work into high-quality data for training, evaluation, and agent development.
Example 01
Evaluate an AI agent performing investment research.
Example 02
Evaluate whether an AI system can reason through complex clinical cases.
Example 03
Assess an AI system's ability to review and interpret commercial contracts.
How it works
We don't start with a resume database.
We start with the work your model needs to accomplish.
We identify the decisions, workflows, tools, edge cases, and failure modes your model needs to handle.
We decompose the workload into the domains, specialties, tasks, skills, and experience required.
We identify, recruit, qualify, and organize experts against those requirements, including narrow and highly specialized fields.
Experts perform real work and evaluate model outputs. Their judgment becomes training data, environments, rubrics, evaluations, and reward signals.
What experts enable
Expert demonstrations, annotations, reasoning, decisions, and domain-specific workflows.
Expert-designed benchmarks, rubrics, judgments, and failure analysis.
Real-world workflows, tools, constraints, and task environments for AI agents.
Human preferences and outcome-based judgments that help models learn what good performance looks like.
Built for frontier AI
The hardest AI problems often require knowledge that can't be found in a standard dataset.
They require people who understand the work.
Alpheva builds specialized expert networks for AI companies working across technical, professional, scientific, and highly specialized domains.
Expertise for model training, reasoning, post-training, and evaluation.
Experts who can perform and evaluate real-world workflows across the tools they use.
Domain specialists who understand the decisions, constraints, and standards of specific industries.
Experts who can distinguish plausible output from genuinely correct, useful, and expert-level work.
Don't see your domain?
If your expertise doesn't fit neatly into an existing category, that's expected.
Tell us what your model needs to learn, perform, or evaluate.
We'll map the required expertise and build the expert network around the work.
Talk to AlphevaBuild with Alpheva
AI systems learn from what they are shown and improve through what they can be measured against.
Alpheva connects AI companies with the specialized human expertise required to generate the data, environments, and evaluations that move models forward.