Microsoft Real Estate and Construction Hong Kong SAR

House730

Enterprise Knowledge Search · Fraud Detection · Risk Management

The city's property market is highly fragmented with many agents restricted to listings within their community.

2023, House730 enjoyed a 30 percent uptick in users who started their property search online first
Between 2021 and 2023, House730 enjoyed a 30 percent uptick in users who started their property search online first, and is now serving an average of more than...
Ultimately, we want to align demand with supply to ensure that no enquiry is left behind." Wong observed that many House730 users employ natural language...
With the power of Microsoft Azure, House730 could deploy the NLP model in just 2 to 3 days without involving a software engineer, bringing significant...

Reported impact

Business outcome

As the first property search engine to capitalize upon Microsoft Azure OpenAI Service's natural language processing in Hong Kong, House730 helps more people house-hunt for their perfect property.

  • Cost Reduction
  • Customer Experience
  • Revenue Growth
  • Risk Reduction

Solution

House730 built its solution on Azure OpenAI Service, Azure AI Foundry, Power Platform to automate high-friction work and turn enterprise data into faster decisions. The implementation combines cloud application services, data services, and AI capabilities so business users can search, summarize, analyze, or act on information through a single digital workflow instead of manual handoffs. It also connects with surrounding systems such as Property listings and agency feeds, which lets the new Azure-based workflow fit into existing operations rather than standing apart from them. As the first property search engine to capitalize upon Microsoft Azure OpenAI Service's natural language processing in Hong Kong, House730 helps more people house-hunt for their perfect property.

Data flow

Content and operational context are prepared in the application data layer, passed to Azure OpenAI for generation or extraction, stored in Azure storage services, and returned through the user-facing application to employees or customers with grounded responses.

Solution architecture

3 components · 2 layers
  1. Compute
    • Azure OpenAI Service Runs large language model inference for summarization, extraction, conversational AI, and grounded answers.
  2. Orchestration
    • Azure AI Foundry Provides the managed environment for model orchestration, experimentation, and responsible AI operations.
    • Power Platform Provides the low-code automation and application platform for workflow modernization.

Architecture clues

  • Uses Azure OpenAI for grounded generation or large-scale extraction workloads.

Evidence from the source

As the first property search engine to capitalize upon Microsoft Azure OpenAI Service's natural language processing in Hong Kong, House730 helps more people house-hunt for their perfect property.
Microsoft Azure OpenAI Service's biggest selling point is that it allows House730 to easily map its own unique format for complete customization.
The city's property market is highly fragmented with many agents restricted to listings within their community.
This was the dilemma we faced." Mike emphasized that the House730 platform is simple, "We want to help people find the right property based on the search criteria entered." To address the five percent of legitimate property searches that...
With the power of Microsoft Azure, House730 could deploy the NLP model in just 2 to 3 days without involving a software engineer, bringing significant administrative and labor cost savings.
Transparency Evidence & methodology 86/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value86/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    House730 customer story

    First-party
    https://www.microsoft.com/en/customers/story/1779424068755514938-house730-azure-other-en-hong-kong-sar
    Source type
    Vendor-published customer story
    Published
    Jun 14, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jun 14, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.