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AWS Real Estate and Construction Japan

Takenaka Corporation

Application Refactoring · Real-time Analytics

Takenaka needed to raise productivity and work efficiency in construction despite labor shortages, overtime limits, and fragmented construction-site data, so it could digitize operations and use business data more effectively.

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applications developed on AWS 100+
months to develop a digital construction solution 19
overtime work to 45 hours per month per employee
productivity has remained almost flat for the past 20 years

Reported impact

Business outcome

Takenaka launched the digital construction solution in 19 months, built more than 100 applications on AWS, improved the use of construction business data, and established a shared platform for digitizing operations across the company.

  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

Takenaka built a digital construction solution on AWS as the foundation of its broader business transformation and to address low productivity, skilled-labor shortages, and stricter overtime limits in construction. The platform combines data collection, AI, BI, and IoT functions so internal teams can rapidly create applications that digitize work across construction sites and corporate operations. Construction data is collected into Amazon S3 and Amazon RDS, integrated with AWS Glue and Amazon Redshift, streamed through Amazon Kinesis for timely processing, and applied to AI and digital-twin use cases with Amazon SageMaker and AWS IoT TwinMaker. This shared data and application layer lets Takenaka develop more than 100 AWS-based applications, support advanced use of construction business data, and accelerate digital-solution delivery across the company.

Data flow

Construction and business data is collected into Amazon S3 and Amazon RDS, prepared with AWS Glue and Amazon Redshift, streamed via Amazon Kinesis, and then used by Amazon SageMaker and AWS IoT TwinMaker to power digital-construction applications across Takenaka.

Solution architecture

7 components · 4 layers
  1. Ingest
    • AWS Glue Integrates and prepares data for analytics and application use.
    • Amazon Kinesis Processes time-sensitive streams inside the digital construction platform.
  2. Compute
    • Amazon SageMaker Supports AI capabilities in the digital construction solution.
  3. Storage
    • Amazon S3 Stores construction and business data for the digital construction platform.
    • Amazon RDS Supports relational data needs in the digital construction solution.
    • Amazon Redshift Provides the analytics warehouse that supports BI use cases.
  4. Serving
    • AWS IoT TwinMaker Supports digital-twin use cases for construction operations.

Architecture clues

  • Built as the foundation for company-wide digital transformation launched in November 2021.
  • Combines data collection, AI, BI, and IoT functions in one digital construction platform.
  • Targets both construction-site operations and corporate business data use.

Evidence from the source

The digital construction solution efficiently develops applications that are necessary for digital transformation by implementing data collection, artificial intelligence (AI), business intelligence (BI), and Internet of Things (IoT) functions.
applications developed on AWS 100+
improving work efficiency and productivity through digitalization is essential for the company to grow.
months to develop a digital construction solution 19
Transparency Evidence & methodology 100/100 reference value · 87% 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 value100/100
  • 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 specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • 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
    4 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • 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. AWS

    Takenaka Corporation customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/takenaka-case-study/
    Source type
    Vendor-published customer story
    Published
    Feb 19, 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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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