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Challenge

Hotel Construction Document Extraction Pipeline with Google ADK

Accor and Al-Qimmah's planned 4,000-room portfolio across Saudi Arabia requires rapid parsing of heterogeneous architectural and regulatory submittals. Build a document intelligence extraction pipeline using Google ADK and Upstage to parse multilingual blueprints and permits. Achieve 98% recall on bilingual key metadata extraction.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build a multimodal document processing agent using Google ADK and Upstage Layout Analyzer to extract structural metadata from submittals.

Delivery guide

How work is evaluated

Evaluation

Evaluates precision and recall of bilingual document metadata extraction from construction submittals.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

permit_number_format_check

Verifies permit number follows standard KSA municipal string patterns

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

metadata_extraction_recall

Recall metric across all required architectural fields • target: 0.98 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Construct a Google ADK agent integrated with Gemini 2.0 multimodal capabilities

  • Leverage Upstage Document AI for layout-aware document extraction

  • Extract bilingual (Arabic/English) room dimensions, zoning approvals, and MEP specs

  • Validate extracted JSON schemas against Saudi Ministry of Housing regulatory requirements

Resources and assets

Reference links and supporting material

Dataset notes

50 synthetic bilingual construction submittals and hotel floor plans formatted as multi-page PDFs.

How this agent runs

Evaluates precision and recall of bilingual document metadata extraction from construction submittals.

Challenge input

PDF file stream or base64 encoded document image

Google ADK

Provides seamless integration with Vertex AI multimodal models.

Upstage

State-of-the-art layout awareness and OCR quality for complex submittal packages.

Evaluated output

JSON object with extracted key-value pairs and confidence scores

Checks for
  • Verifies permit number follows standard KSA municipal string patterns
  • Recall metric across all required architectural fields • target: 0.98 • range: 0-1
Proof of success
  • Benchmark: DocVQA-Bilingual
  • Metadata Extraction Recall target: 0.98
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Google ADK · Required
  • Google · Optional
  • Upstage · Optional

Evaluation contract

  • permit_number_format_check · Weight 1
  • metadata_extraction_recall · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Hotel Construction Document Extraction Pipeline with Google ADK