{
  "@context": "https://schema.org",
  "@type": "QAPage",
  "canonical": "https://ireadcustomer.com/en/blog/how-onestruction-built-the-ishigaki-ids-foundation-model-with-aws-genaiic",
  "markdown_url": "https://ireadcustomer.com/en/blog/how-onestruction-built-the-ishigaki-ids-foundation-model-with-aws-genaiic.md",
  "title": "How ONESTRUCTION Built the Ishigaki-IDS Foundation Model with AWS GenAIIC",
  "locale": "en",
  "description": "Discover how ONESTRUCTION collaborated with the AWS Generative AI Innovation Center to build Ishigaki-IDS, a groundbreaking foundation model for BIM and construction.",
  "quick_answer": "ONESTRUCTION built the Ishigaki-IDS foundation model for BIM and construction workflows with AWS GenAIIC by combining synthetic data, a three-stage training pipeline, and verifiable rewards on Amazon EC2, reducing manual layout generation times by up to 80%.",
  "summary": "Building custom artificial intelligence models with high precision in data-scarce industries is no longer an impossibility. The collaboration between ONESTRUCTION, a Japanese construction technology pioneer, and the AWS Generative AI Innovation Center (GenAIIC) has proved this by developing the onestruction ishigaki ids foundation model . This domain-specific large language model is tailored specifically for Building Information Modeling (BIM) workflows, enabling organizations to process complex structural blueprints efficiently using scalable, cost-effective cloud technologies. This architect",
  "faq": [
    {
      "question": "What is the Ishigaki-IDS foundation model?",
      "answer": "Ishigaki-IDS is a domain-specific foundation model built by ONESTRUCTION in collaboration with the AWS Generative AI Innovation Center. It is specifically trained and optimized to understand construction workflows, architectural physics, and Building Information Modeling (BIM) structural designs."
    },
    {
      "question": "Why do standard LLMs fail at construction tasks?",
      "answer": "Standard language models treat blueprints as simple text or flat images. They fail to understand physical limitations, spatial 3D relationships, and materials load-bearing constraints, which causes them to hallucinate impossible structural layouts and fail local regulatory and safety standards."
    },
    {
      "question": "How did synthetic data help build this foundation model?",
      "answer": "Because real-world construction blueprints are proprietary and highly confidential, ONESTRUCTION used parametric programming rules to generate high-fidelity synthetic layouts. This programmatically created vast training datasets containing accurate architectural components without violating client privacy."
    },
    {
      "question": "What is the purpose of the three-stage training pipeline?",
      "answer": "The three-stage training pipeline ensures structured learning. It starts with Continued Pre-training to absorb general technical and engineering vocabularies, followed by Supervised Fine-Tuning for task-based design instruction, and ends with Reinforcement Learning with verifiable rewards to optimize output safety."
    },
    {
      "question": "How does this custom AWS solution compare to generic SaaS software?",
      "answer": "Generic SaaS tools present rigid features and recurring licensing costs while risking data leakage. In contrast, custom model integration on AWS grants the enterprise full model ownership, protects proprietary workflows, allows continuous updates, and creates unique, defensible IP assets."
    }
  ],
  "tags": [
    "aws genaiic",
    "onestruction ishigaki-ids",
    "bim foundation model",
    "synthetic data construction",
    "amazon ec2 ai training"
  ],
  "categories": [],
  "source_urls": [
    "https://aws.amazon.com/blogs/machine-learning/how-onestruction-built-the-ishigaki-ids-foundation-model-with-aws-genaiic"
  ],
  "datePublished": "2026-08-29T08:05:45.425Z",
  "dateModified": "2026-08-29T08:05:45.453Z",
  "author": "iReadCustomer Team"
}