You are choosing where your company's knowledge will live once staff start asking AI questions about it: inside Microsoft, inside Google, inside a specialist search platform, inside OpenAI, or on infrastructure you control. Here is what that decision actually turns on for a Hong Kong enterprise with 100 to 500 staff.
This page compares five realistic options on price, data location, model choice and the limitation most likely to stop the purchase. Prices were checked on 30 September 2026 against vendor pages and dated third-party pricing reviews, which are linked so your procurement team can verify them.
What is an enterprise AI knowledge base, and what are you actually buying?
An enterprise AI knowledge base is a system that indexes internal documents such as SOPs, contracts, product specifications and meeting minutes, then lets staff ask questions and receive cited answers within their access permissions. You are buying three things: a retrieval layer, a model to answer, and controls over where the data sits.
Most buying mistakes come from comparing the chat interface and ignoring the other two layers. The questions that separate the options are:
--- Data location: does indexed content stay in your tenant, the vendor's cloud, or your own servers?
--- Model choice: are you locked to one model family, or can you switch?
--- Permissions: does the system respect existing folder and role access automatically?
--- Pricing basis: per seat, per usage, or a project quote?
Which enterprise AI knowledge base options should a Hong Kong firm shortlist in 2026?
Five options cover most Hong Kong enterprise needs in 2026: Microsoft 365 Copilot, Google Gemini Enterprise, Glean, OpenAI's enterprise platform with its new Private Intelligence controls, and a privately deployed knowledge base such as UD's Private AI BizHub. They differ most on data location, model choice and whether pricing is published.
Microsoft 365 Copilot
Answers from content already in SharePoint, OneDrive, Teams and Outlook, inside your Microsoft 365 tenant. The enterprise add-on is listed at US$30 per user per month; our Copilot alternatives guide covers the 2026 bundle changes in detail. Strongest when your documents already live in Microsoft.
Google Gemini Enterprise
Google Cloud's agent and enterprise search platform, with connectors to Workspace, Microsoft 365, Salesforce, ServiceNow and Jira. GoSearch's July 2026 pricing review lists Business at about US$21, Standard at about US$30 on an annual term, and Plus at about US$50 to US$60 per user per month.
Glean
A specialist enterprise search and assistant platform with broad connectors and permission-aware answers. Glean does not publish prices. Workativ's 2026 pricing analysis reports a median of about US$50 per user per month for the base seat, roughly US$15 more for AI add-ons, minimums of 50 to 100 seats, and entry contracts around US$60,000 a year.
OpenAI enterprise platform with Private Intelligence
At DevDay on 29 September 2026, OpenAI grouped its data controls under the name Private Intelligence. According to OpenTools' breakdown, zero data retention with Private Safety Processing is rolling out in phases for approved API projects, while Private Inference is only a preview with no availability date. Enterprise pricing is quote-based.
Private AI BizHub (UD)
A knowledge base deployed on your internal servers or private cloud, built on GPU infrastructure, that imports Word, PDF and Excel files, applies role-based access and lets you switch between models including ChatGPT, Claude Opus, Gemini and DeepSeek. UD does not publish a product price; it is quoted after a free demo.
How much does an enterprise AI knowledge base cost for 200 staff?
For 200 staff, published or reported list prices put Microsoft 365 Copilot and Gemini Enterprise Standard at about US$72,000 a year each, and Glean at roughly US$156,000 including AI add-ons. OpenAI Enterprise and a private deployment are quote-based, so their cost depends on usage, infrastructure and scope rather than seats alone.
The illustrative annual figures below multiply list or reported per-seat prices by 200 users for 12 months, converted at about HK$7.8 to the US dollar. They exclude discounts, implementation and existing licences.
--- Microsoft 365 Copilot: 200 x US$30 x 12 = about US$72,000 (about HK$562,000), on top of the Microsoft 365 licences you already pay for.
--- Gemini Enterprise Standard: 200 x US$30 x 12 = about US$72,000 (about HK$562,000); custom agents built on the underlying platform are billed separately by usage.
--- Glean: 200 x (US$50 + US$15) x 12 = about US$156,000 (about HK$1.22 million), based on third-party estimates, plus a reported support fee.
--- OpenAI enterprise: quote only.
--- Private AI BizHub: quote only; infrastructure and GPU capacity are part of the scope.
Seat pricing punishes low adoption: you pay for every assigned seat whether or not it is used. Private deployments shift cost from seats to infrastructure, which favours organisations where many staff ask occasional questions. Our private AI versus cloud cost analysis sets out the break-even arithmetic.
Why do Hong Kong enterprises switch away from public AI knowledge tools?
Hong Kong enterprises usually switch for four reasons: client or regulatory pressure to keep documents on infrastructure they control, a need to use more than one AI model, poor handling of Traditional Chinese and mixed-language files, and seat costs that grow faster than adoption. Data location is typically the trigger that starts the review.
--- Data location: law firms, insurers, family offices and healthcare groups increasingly receive client questions about where AI processes their documents. A contract answer is weaker than an architectural one.
--- Model lock-in: suite products tie you to one model family. After this quarter's model withdrawals, many risk committees now ask for a tested alternative, as our guide to AI model concentration risk explains.
--- Language: archives full of Traditional Chinese contracts, scanned forms and bilingual minutes need testing on your own files, not a vendor demo set.
--- Cost shape: per-seat bills scale with headcount, not with value delivered.
Where do the global platforms beat a private deployment?
The global platforms beat a private deployment on speed to launch, depth of integration with the apps staff already use, breadth of connectors, and published pricing. A private deployment such as Private AI BizHub wins on data control and model choice but asks more of your infrastructure and procurement process. Neither choice is free of trade-offs.
Where the global platforms win:
--- Inside the apps: Copilot works directly in Word, Excel, Outlook and Teams; Gemini does the same in Workspace. A private knowledge base is a separate interface.
--- Connector breadth: Glean and Gemini Enterprise advertise wide SaaS connector libraries; UD does not publish a connector list, so confirm yours in the demo.
--- Published prices: Copilot and Gemini publish list rates, which makes budget approval faster.
Limitations of Private AI BizHub to weigh honestly:
--- No published price: you cannot budget from the website; a quote follows the demo.
--- Infrastructure required: deployment is on your servers or private cloud, so you need hosting capacity or a partner to run it.
--- Offer terms: the demo bonus is labelled limited-time with no published end date.
--- Security is shared: private means controllable, not automatically safer; patching and access control remain your responsibility or your partner's.
Which option should each type of buyer choose?
Choose Copilot if your documents already live in Microsoft 365, Gemini Enterprise if you run on Google Workspace or want an agent builder, Glean if you have 500 or more staff and many SaaS systems, OpenAI's platform if you are building your own applications, and a private deployment if documents must stay on infrastructure you control.
--- Microsoft-centric firm, 100 to 500 staff: start with Copilot; the integration advantage is decisive if SharePoint is well organised.
--- Google Workspace organisation: Gemini Enterprise Standard, and budget separately for any custom agents.
--- Large, multi-system enterprise with a US$60,000 or larger budget: Glean is built for this scale.
--- Engineering-led team building AI into its own products: OpenAI's API with zero data retention, and wait for Private Inference details before relying on it.
--- Regulated or confidentiality-bound firm in Hong Kong: shortlist a private deployment such as Private AI BizHub alongside one suite option, and let a pilot on your own documents decide.
What should you ask in a demo before signing?
Before signing, ask every vendor where indexed data and logs are stored, who holds administrator access, how existing permissions are mapped, which models can be used, what happens to your index if you cancel, and how accurately the system answers questions from your own Traditional Chinese documents. Written answers are the only ones that count.
Bring 20 real questions and the documents that answer them to every demo, including at least five in Traditional Chinese. Score each vendor on accuracy, citation quality and whether restricted documents stayed hidden from a test account without access.
Migration effort matters too. Moving from one suite to another usually means re-indexing and re-mapping permissions, typically weeks rather than days for a 200-person firm. Ask each vendor for a written migration plan and exit terms.
Finally, agree the pilot scope before the demo ends. A four-to-six-week pilot with one department, one document collection and a named business owner produces evidence your CFO can review. Define success in advance: answer accuracy on the 20 test questions, time saved per query, and the share of pilot users still active in the final week. Without those three numbers, the pilot becomes a preference vote rather than a decision.
Private AI BizHub: quick facts
--- Deployment: internal servers or private cloud, on GPU infrastructure.
--- Inputs: Word, PDF and Excel documents, indexed automatically.
--- Access: answers follow each user's AI permissions.
--- Models: switchable, including ChatGPT, Claude Opus, Gemini and DeepSeek.
--- Price: not published; quoted after a free demo.
--- Current offer: booking a demo includes a free enterprise Cloud Security Assessment valued at HK$10,000; limited-time, end date not published.
--- How to start: book the demo on the Private AI BizHub page; no payment card is required.
Conclusion: decide on data location first, then features
Every platform on this list can answer questions from documents. What separates them is where your data sits, which models you can use and how the bill scales. Settle the data-location question with your risk and legal teams first, shortlist one suite option and one private option, and run both on your own files before you sign.
We understand the cold edges of AI and the hard parts of your work, and UD has walked with Hong Kong enterprises for twenty-eight years, making technology a partnership with warmth.
Reviewed by the UD enterprise AI team. Prices and features were checked on 30 September 2026 against vendor pages and the dated third-party reviews linked above. Vendors change plans often, so confirm before buying.
See a Private Knowledge Base Running on Your Documents
Book a free Private AI BizHub demo and receive a free enterprise Cloud Security Assessment valued at HK$10,000. We'll walk you through every step, from choosing test documents and mapping permissions to deployment options and a written quote.
