A Zhipu AI headquarters visit puts a delegation inside the first company to list on a public market with a general-purpose AI foundation model as its core business. The Beijing programme runs at the company's headquarters — a showroom walk through its development history and product matrix, followed by structured sessions on large-model trends, enterprise readiness and implementation. What a management team takes home is not a technology demo. It is how a research spin-out from Tsinghua University built a usable model stack, priced it, and turned a lab capability into a commercial platform serving millions of customers and developers.
Key takeaways
Zhipu AI was established in 2019 out of Tsinghua University's knowledge-engineering work, and in January it listed on the Hong Kong Stock Exchange as the first public company whose core business is a general-purpose AI foundation model.
The reason to go is the full-stack position: the company develops the GLM pre-training architecture itself, has adapted it to more than forty domestic chips, and sells access through a model-as-a-service platform rather than only through bespoke deployments.
The headline exhibits are the GLM model family and the product matrix around it — development tools, application platforms and industry solutions — presented together rather than as separate products.
The business story is a commercialisation arc, not just a research record: three consecutive years of doubling revenue, a customer and developer base in the millions, and a pricing model built on API consumption.
We arrange the programme end to end, including site scheduling on the Chinese side, transfers within Beijing and English interpretation on site, with sessions shaped around your delegation's own adoption questions.
Key visit details
Where the visit is held
Location — Zhipu AI's Beijing headquarters, or a designated innovation and demonstration centre, depending on the schedule agreed with the company. The visit is normally one day, and a half-day version can be arranged.
Getting there — the site sits in Beijing's technology district, and we plan the transport as part of the programme, including pickup from your hotel. Exact meeting arrangements are confirmed with the company ahead of the visit.
Format and duration
Duration — One day by default, structured as a showroom walk followed by two themed sessions with a break, and optionally extended to a two-day deep version.
Format — A guided showroom walk covering the development history, brand, product matrix and business layout; a session on large-model trends and generative-AI fundamentals; and a session on industry application and business innovation, both with question time.
Who the programme suits
Best suited to — Executives and strategy teams assessing AI adoption; digital-transformation and IT leadership; business-unit heads looking for concrete use cases; AI, data and cloud practitioners; and investors and researchers following China's model ecosystem.
Main themes — Foundation-model technology, model-as-a-service economics, domain deployment, AI governance and compliance, and how enterprises move from pilots to scaled use.
Booking, group size and site rules
Booking — Around 30 days in advance is the practical lead time, because the programme involves company specialists and internal scheduling. The programme is best suited to groups of 10–20 participants.
Site rules — Photography and recording follow the host's instructions in each area. Specific requirements are confirmed before you travel rather than on the day.
Why a Zhipu AI visit is worth a delegation's day
The scale alone justifies the trip. Zhipu's GLM models have been applied across internet, consumer electronics, industrial manufacturing, energy, public services, finance, telecommunications and education, and nine of China's ten largest internet companies use them. The company has raised more than eight rounds of funding totalling over eight billion yuan before listing, and its models reach thousands of enterprise customers and millions of developers.
The more useful object of study is the commercial model rather than the benchmark. Most AI companies in China began as project businesses — custom deployment for a large client, then another. Zhipu's bet is the opposite: build one model, expose it through an API, and let volume carry the economics. Reading that in a prospectus tells you the strategy. Hearing the company explain how it prices, what it counts as retention and where the margin sits tells you whether the model is actually working.
The second reason is the domestic-chip question. GLM has been adapted to more than forty domestic processors, which is a supply-chain position as much as a technical one. For any delegation whose own AI plans depend on hardware availability, that adaptation work is the least glamorous and most consequential part of the story. Delegations combining the visit with other Beijing AI sites can use the Beijing tech tour page, and the company visits index sets out the wider portfolio.
Inside the Zhipu AI showroom
The showroom covers the company's development history, brand, product matrix and business layout. Four threads carry most of the weight for a visiting team.
The GLM model family
The GLM series. The exhibits walk through the model generations and the shift to a design that fuses reasoning, coding and agent capability inside a single model rather than splitting them across specialists. For a visiting engineering team the useful question is how the company manages a two-to-three-month iteration cycle without breaking the customers built on the previous version.
Multimodal and vision models
Multimodal capability. Vision models that understand images and documents sit alongside the language models, with long context handling and native tool calling. The exhibit matters most to teams whose data is not clean text — manufacturing, healthcare, finance — where the real work is extracting structure from documents and photographs.
Agents and application-level APIs
Agent models and applications. The company presents models built specifically for planning, reasoning and execution rather than chat, alongside pre-built application APIs for translation, document generation and presentation design. This is the clearest view of where the industry is heading: from answering questions to completing tasks.
The MaaS platform and the product matrix
Model-as-a-service. The platform view shows how developers and enterprises consume the models — development kits, application platforms, industry solutions and the API billing behind them. For a commercial delegation, this is the stop that answers the least romantic and most important question: what does enterprise adoption cost, and who pays.
The two themed sessions
The sessions are the substantive part of the day, delivered by company experts or business leads rather than general guides. A half-day version compresses them into one.
Large-model trends and generative-AI fundamentals
Session one covers the development path of AI and large models, the frontier applications and industry landscape, the core principles and key techniques behind large language models, how to assess an organisation's readiness for adoption, and the security and compliance framework an enterprise needs around it. The readiness assessment is the segment most useful to non-technical leadership.
Industry application and business innovation
Session two moves from theory to implementation: how to surface AI requirements and identify the scenarios worth building, the general architecture that fits most industries, the project flow with its key checkpoints and risks, and how to run large-model use as a long-term capability rather than a one-off project.
Alternative session topics
Tailored modules. Sessions can be swapped for deeper technical material — in-depth model exploration and optimisation, a full application-development walk-through, an efficiency programme moving from tools to systems, prompt engineering from beginner to advanced, or a session on compliance, ethics and regulation. Tell us your sector and the session is shaped around it.
What different teams take away
For executives and strategy teams — how to assess whether an organisation is ready for large-model adoption, where the real cost sits, and how to sequence investment rather than scattering pilots.
For IT and digital-transformation leadership — the architecture question: what to run in the cloud, what to keep on premises, how to manage data governance, and what compliance obligations attach to model use.
For business-unit heads — how requirements are surfaced and scenarios selected, with cases from finance, government, manufacturing, healthcare and education that can be mapped onto your own operations.
For AI and data practitioners — model capability, iteration cadence, tool calling and agent design, and how a domestic-chip adaptation programme constrains and enables what can be built. The same sessions should land differently for each group, and we shape them around whichever one your delegation is.
Sample visit programme
| Time | Session | What to expect |
|---|---|---|
| 09:30 | Showroom walk | Development history, brand and culture, the product matrix and the business layout, with a company guide and time for questions. |
| 10:30 | Session one | Large-model trends and generative-AI fundamentals: the technology path, the industry landscape, model principles, readiness assessment and the security and compliance framework. |
| 13:30 | Session two | Industry application and business innovation: surfacing requirements, the general deployment architecture, project flow with its risks, and running adoption as a long-term capability. |
| 16:30 | Close | Wrap-up discussion and departure, with the option of a further tailored module on a two-day version. |
The point of the visit is not the model on the screen. It is understanding what has to change inside your own organisation before the model is useful.
Practical notes for the day
Come with a use case. The sessions are most valuable when the delegation arrives with one or two concrete processes in mind. Generic attendance produces a generic day; a specific case gets specific answers about data, architecture and cost.
Mix the delegation. The day pays off most when technical and business people attend together, because the readiness and architecture questions only resolve when both perspectives are in the room.
Send questions in advance. The sessions are the part of the day most sensitive to preparation, and handing over your questions a week ahead produces a session that engages with them directly.
Interpretation matters. The vocabulary of model architecture, inference cost and agent design does not survive casual translation, which is why interpretation on site is handled by people who work on these visits.
Questions before a Zhipu AI visit
Where is the visit held? At Zhipu AI's Beijing headquarters, or a designated innovation and demonstration centre, depending on the schedule agreed with the company.
How long does the visit take? One day by default, with a half-day version available and a two-day deep version for groups wanting more technical material.
Are the sessions technical or business-oriented? Both. The default programme pairs a technical session on models and generative AI with a business session on industry application and implementation, and either can be weighted depending on your group.
Can the topics be tailored? Yes. Sessions can cover model optimisation, application development, efficiency programmes, prompt engineering or AI compliance and regulation, adjusted to your sector.
Is this suitable for non-technical executives? Yes. The readiness assessment and the industry case work are built for leadership groups, and the technical session is pitched to be usable without an engineering background.
What group size works best? The programme is best suited to groups of 10–20 participants. We charge per group, so larger groups usually offer better value per person. Individuals and smaller groups are welcome to enquire at a higher per-person rate. Larger delegations can be split across sessions if that suits the schedule.
Is English interpretation provided? Yes. English interpretation on site is part of how the programme is run, including during both sessions.
How far in advance should we book? Around 30 days is the practical lead time, because the programme involves company specialists and internal scheduling.
Does the programme always run as described? It is built around the elements above. Facilities and areas opened on the day are subject to what the site opens, and we confirm the final scope in writing during planning, before you commit.
Arranging your Zhipu AI visit
We arrange the visit for you end to end: the introduction to the host, the scheduling on the Chinese side and English interpretation on site. Tell us your dates, your delegation size, your sector and the use cases you want to discuss, and we will confirm what can be arranged. Start at chinatechvisits.com/company-visits.