About Us

Quneryva was created by Dmytro Cherednichenko, a recruiting education specialist with 5 years of experience in hiring workflows, candidate communication, role research, interview planning, and AI-supported recruiting processes. Throughout his work, Dmytro repeatedly noticed the same challenge: recruiting teams were interested in using AI, but many available materials were either highly technical or disconnected from everyday hiring responsibilities.

Recruiters often had to collect information from separate sources and then work out how each idea related to real tasks. Role descriptions, candidate messages, interview questions, evaluation notes, and team handovers were frequently treated as unrelated topics. Dmytro believed that learners needed a structured route showing how these elements connect across a complete recruiting process.

This observation became the starting point for Quneryva.

The first course materials were developed around practical questions raised by recruiters and hiring coordinators. How should a role brief be organised before preparing new materials? What information should be included in candidate communication? How can interview questions remain connected to stated role criteria? What should a recruiter review before using an AI-generated draft?

Dmytro organised these questions into clear learning modules, guided activities, review checklists, and realistic recruiting scenarios. Instead of presenting AI as a replacement for human judgment, Quneryva explains how it may assist with drafting, organisation, research preparation, and documentation. Candidate evaluation, communication approval, and hiring decisions remain with people.

Our Learning Direction

The Quneryva curriculum covers foundational AI concepts, prompt planning, role research, candidate communication, interview preparation, resource organisation, reporting, workflow design, and revision management. Each course focuses on a defined area of recruiting work and explains the topic through structured written materials.

Learners are encouraged to examine context before beginning a task. They review whether the information is current, whether the wording is suitable, and whether the material reflects the stated hiring criteria. This approach helps learners build careful working habits rather than rely on fixed instructions that may not fit every role.

Every module includes practical elements such as worksheets, planning pages, sample hiring documents, comparison activities, and reflection questions. These materials help learners connect the course topics with responsibilities they may already handle in their work.

About Dmytro Cherednichenko

Dmytro has spent five years working with recruiting processes, educational materials, and AI-supported workflow planning. His background includes role intake preparation, recruiting documentation, candidate communication, interview structure, hiring data organisation, and internal process review.

During this period, he worked with recruiting teams, hiring coordinators, team leads, and learners from different working environments. This experience gave him a detailed understanding of where hiring information may become unclear, repeated, outdated, or disconnected between stages.

His work has focused on helping teams document responsibilities, organise recurring tasks, prepare review steps, and maintain human oversight throughout hiring activities. He also studies how written instructions influence AI-generated materials and how those drafts can be checked for factual gaps, unclear language, and unsupported assumptions.

Dmytro has taught more than 1,000 learners through structured educational materials and guided learning programs. Learner questions have played an important role in the development of Quneryva. Their feedback helped refine explanations, expand examples, improve worksheets, and create clearer links between individual recruiting topics.