Why IRBIS exists.
IRBIS is built by researchers in Kazakhstan for institutions that take their data seriously.
How IRBIS came to be.
Researchers were already pasting data into chatbots
The habit was invisible to the institution and impossible to audit. Banning AI didn't stop it — it just moved it to personal accounts.
Govern the workspace, not the researcher
Give people a better tool than the chatbot: real engines, real methods, AI assistance that works through vetted operations and never touches a raw row.
A firewall you can show your data-protection officer
Column classification, aliasing, small-cell suppression, and a content-hashed audit log — designed with local data law in mind, documented in EN / RU / KK.
From field data to published, reproducible findings
Manuscripts rebuild from deterministic artifacts. Institutions get proof, researchers get speed, and nobody trades one for the other.
What we hold to
The data stays home
Raw rows live server-side, always. AI sees aliases and aggregates — never individuals.
Engines, not arithmetic by LLM
Every statistic comes from R, Python, or Stan. The AI orchestrates; it never computes results.
Provable, not promised
Every operation is logged with its policy result. Audits are a feature, not an interruption.
Three languages, one standard
English, Russian, and Kazakh are first-class across the product and its reports.
Reproducible by construction
Findings rebuild from artifacts. If a result changes, IRBIS says so — and why.
Built where it's used
Priced for institutions in the region and aligned with local data law.
The irbis moves through the high mountains — seldom seen, never careless. We named the platform after it because serious research is the same kind of work: it survives on precision, patience, and leaving a clean trail behind you.