Turns data scattered across your systems into one no-code data hub and models it into a shared semantic layer — the same reality for people and agents, and the foundation of the tsan.ai stack.
An AI Engine (cognition / execution / decision-making) + a Knowledge Hub (multi-source connectors, knowledge pipelines) + a Model Factory (model repository, eval benchmarks) — the reasoning infrastructure beneath the ontology.
50+ relational and non-relational databases, 10+ IoT protocols (covering 90%+ of scenarios), and 60+ intelligent ETL algorithms bring scattered data into one ontology.
Data standards, asset management, and end-to-end quality and security controls turn raw records into trusted assets.
Models business objects, rules, and org structure into one AI-readable, executable semantic layer — the ontology's core capability.
A standardized API connects DeepSeek, Qwen, Claude and other leading models, orchestrating tens of billions of parameters in parallel — swap models freely, never locked in.
AI-driven analytics on top of the semantic layer — time-series forecasting, multi-dimensional attribution — feeding decisions to every agent and app above it.
tsanCenter used to mean one bespoke model per project. As an ontology, the standard-setting stage now distills a minimal, cross-industry, reusable meta-model — objects, relations, rules — the precondition for the dark factory to mass-produce instead of remodeling every project from scratch.
Distill a minimal, reusable meta-model — objects, relations, rules
Collect, clean, tag, enrich, clear rights, QA — a human-AI hybrid workflow
A semantic modeling engine and a rule engine write into one unified ontology
Exposed via MCP-style interfaces — callable by people and agents alike
Many organizations aren't ready for AI because the step before it — digitalization — was never finished: systems everywhere, data scattered across silos, business rules that live only in documents and tribal knowledge. tsanCenter turns those three foundations into a reusable platform.
Microservices plus low-code/no-code configuration compress delivery from months to weeks — the starting point of tsanCenter's decade of engineering, proven repeatedly in real media, government, and education projects.
Consolidates data across systems into an enterprise-grade hub matrix — a user hub, data hub, AI hub and more. The same ten-module architecture is proven in real deployments like provincial media-convergence platforms, breaking down the data silos between departments and systems.
Models business rules, approval flows, and org structure into one executable business-object system — replacing the tacit knowledge locked in documents and individual experience, and forming the base the semantic ontology layer builds on for every agent and app above it.