Before any preparation work starts, we search public material, indicators, samples and corpora to locate usable sources. We then assess availability and compliance boundaries, so you commit only to what is feasible.
Raw material often arrives scattered and inconsistent. We clean and de-duplicate it, align fields and convert formats — turning heterogeneous data into a structure you can keep working with, not a one-off export.
For research, industry analysis and enterprise governance, we build structured tables and multi-year panels with clearly named fields and consistent definitions — so you can reproduce results and take the analysis further.
For training, evaluation, RAG and agent scenarios, we prepare corpora, samples, labels and supporting documentation — covering every stage from pre-training data through to preference alignment.
Every delivery ships with field descriptions, source notes, a record of missing or anomalous values, and clearly stated acceptance boundaries. You can review each item, sign it off independently, and keep using it with confidence.
Built around the specific goals of enterprise, research and AI teams — never a fixed template. Data tables, sample files, delivery notes and follow-up support are packaged and delivered together.
