Klynk Information

We build the data, tasks, benchmarks and evaluation systems that help AI models become better at real-world work. Our work focuses on creating high-quality training and evaluation signals for modern AI systems from coding and reasoning tasks to agent workflows, model response evaluation and automated verification. We work with engineers, researchers and domain experts to build tasks that are: * Expert-authored * Clearly specified * Verifiable * Reproducible * Designed to measure real capability Our work includes: → Coding & software-engineering tasks → SFT and preference data → RLHF / human feedback → Model response evaluation → Benchmark development → Agent and tool-use tasks → Docker-based evaluation environments → Reference solutions and automated tests → Rubrics, graders and verification systems → Technical QA and failure analysis We believe better AI requires more than bigger models. It requires better training signals, harder tasks, stronger evaluations and reliable ways to measure what models can actually do. We are building that layer.