TIDENET (BEIJING) TECHNOLOGY CO., LTD. has won the contract for Cultural Relics Press's high-quality dataset project. Building on the press's more than sixty years of archaeological publishing, the project will create thematic datasets and a RAG knowledge base covering every field of early Chinese civilization. It is a key move in tsan.ai's work embedding AI-native development in the data infrastructure of vertical industries, and offers a reusable model for the intelligent transformation of the cultural heritage sector.
The tsan.ai platform
Building sustainable data infrastructure "back end first"
Archaeological data is by nature multi-source, heterogeneous and inconsistently standardized, and traditional custom development struggles to keep up with an evolving body of knowledge. What Cultural Relics Press needs is not a system delivered once, but a data foundation that keeps growing as research deepens. That is exactly what the tsan.ai platform is for.
Unlike low-code and AI development tools driven by forms and front ends, the tsan.ai platform goes from the data back end to the front end: it first builds a solid data management and business logic layer so large AI models can read the data and understand the business, and front-end applications can then grow naturally and flexibly. The platform is built around three core capabilities:
- Intelligent data management: large models understand relationships in business data, recommend and optimize data models automatically and quickly build a complete data management back office.
- Business logic orchestration driven by hybrid models: combining rule engines with machine learning to turn complex business scenarios into visual, executable, definable workflows.
- Controlled intelligent development: on top of data management, intelligent development agents can build applications, optimize code and run operations around the clock.
More than 1,500 enterprise-grade application modules have been built on the tsan.ai platform, and intelligent solutions based on it have taken on several large AI transformation projects, more than half of which have been delivered — proof of the platform's stability and efficiency in real business.
Three flexible layers
Data infrastructure that grows with the business
In the Cultural Relics Press project, the platform's architecture shows its strengths at three configurable levels:
- Intelligent workflows: the data processing pipeline (collection, cleaning, annotation, enrichment, rights confirmation, quality control and more) builds AI data processing fully into the work, with mixed orchestration of people and agents — agents can even decide how to process each object themselves. This turns the relationship between large models and data into a controlled business process, merges expert knowledge into the workflow and keeps turning experts' knowledge into model capability, creating a living, evolving way of working;
- Build-your-own agents: with the built-in agent management module (tsanClaw), business staff can configure knowledge services for search, Q&A, writing and more without developers, so the people who know the business best define the knowledge applications directly.
- Extensible capabilities: an open node mechanism lets new data sources, annotation strategies and quality-control rules be registered through standard interfaces, so the platform grows as data accumulates.
From data assets to intelligent services
A complete value loop
For the press, the project marks a shift from traditional publishing services to intelligent knowledge services, with clear, concrete changes: archaeological material scattered across paper reports and scans becomes structured assets organized to a single standard; knowledge across themes and periods is at researchers' fingertips; and Q&A verified against the knowledge base and first drafts of reports that follow archaeological conventions greatly speed up research.
More importantly, the capabilities this architecture supports can keep expanding. As data accumulates year by year, the platform grows and evolves with it, and this knowledge foundation opens limitless possibilities for intelligent output in research, teaching, exhibitions and cultural creation.
Beyond archaeology
A model of data infrastructure for many industries
The experience of building data infrastructure in archaeology is equally relevant to other fields with large bodies of industry knowledge. Media, publishing, healthcare, finance, industry and education all face the same problem: "lots of data but inconsistent standards; standards that are hard to apply; and results that are hard to sustain."
The method proven in the Cultural Relics Press project — a low-code platform powered by intelligent development as the foundation, a thesaurus to unify standards, visual pipelines to orchestrate data processing, and agents to package knowledge services — rests on general principles: decouple standard-setting, data processing, knowledge building and service delivery, so industry experts can do specialist work through configuration without going through a development team.
The method brings two kinds of value:
First, data infrastructure moves from a one-off project to a sustainable operating capability: new data sources, new dimensions of knowledge and new forms of service can be added at any time;
Second, industry experts engage directly with data infrastructure: those who set standards configure the thesaurus and those who edit reports build agents, with no intermediary between the people who define knowledge and the people who use it.
From heritage to every industry
The continuing evolution of intelligence
tsan.ai has not stopped at a single platform. tsanClaw, its enterprise-grade platform for AI agent collaboration launched in 2026, takes the AtoA idea of "intelligence creating intelligence" into engineering practice, building a complete loop of intelligent evolution through its four strategies of deep thinking, full sensing, precise action and continual renewal. On this basis, tsan.ai is extending its AI capabilities to telecom operators, the digital technology arms of central and state-owned enterprises, HR and other industries, quickly building demonstrations.
With the tsan.ai platform as its foundation, tsan.ai is using a single architecture to support high-quality dataset building across industries, helping every industry achieve a genuine digital and intelligent renewal in the wave of AI.