BIM Data, QA/QC & Model Intelligence
Improve BIM Data Quality, Consistency and Reliability.
BIM models contain significant amounts of project information, but that information is only useful if it is complete, consistent and reliable. We help project teams validate model data, perform health checks, clean up information and establish structured QA/QC workflows that improve BIM data quality across design, coordination and delivery.
Every engagement starts by understanding the project requirements, BIM standards, LOD/LOIN expectations, model uses and applicable compliance requirements. We then assess the existing model data quality and define the appropriate validation, QA/QC and data management approach.
Our services can include model health checks, data validation, parameter QA/QC, automated model checking, information clean-up and asset data structuring for downstream use in coordination, construction and handover.
The result is BIM information that is more complete, consistent and suitable for its intended use — whether that is coordination, construction, facilities management or client handover.
Model validation, health checks and automated checks that identify data quality issues.
Automated QA/QC workflows that validate BIM data against project standards and requirements.
Structured data clean-up and parameter management to improve model reliability.
Asset information workflows that prepare BIM data for downstream handover and FM use.
Model Health Checks
Model validation and health checks that identify incomplete, inconsistent or unreliable BIM data.
Automated QA/QC
Automated QA/QC workflows that validate models against project standards and requirements.
Data Clean-Up
Structured parameter management and data clean-up to improve model consistency.
Asset Information
Asset data structuring and validation for downstream handover and facilities use.
What the scope covers.
Each area can be taken on its own or combined into a single package, depending on where the gap sits.
Model Health Checks & Validation
- Model element validation
- Data completeness checks
- Naming and standards review
- LOD/LOIN compliance assessment
- Model health reporting
- Issue identification and classification
Automated BIM QA/QC
- Automated model checking workflows
- Clash and standards validation
- Parameter QA/QC automation
- Naming convention checks
- Automated QA/QC reporting
- Workflow integration with Revit and Navisworks
BIM Data Clean-Up & Management
- Parameter clean-up and correction
- Element data standardisation
- Naming and classification alignment
- Duplicate and error removal
- Model data restructuring
- BIM standards alignment
Asset Information Workflows
- Asset data extraction and structuring
- COBie data preparation
- Handover information validation
- FM-ready data workflows
- Asset register preparation
- Information delivery milestone support
Model Intelligence & Reporting
- Model data extraction and analysis
- Information quality reporting
- Data completeness dashboards
- Cross-model data comparison
- Model intelligence insights
- Delivery and progress reporting
What this covers
LOD 100–500
Modelling & Development
8+
Core Coordination Capabilities
360°
Model-to-Delivery Support
Why it is worth outsourcing.
More Reliable BIM Data
Model health checks, data validation and structured QA/QC help identify incomplete, inconsistent or unreliable information before it affects downstream project use.
Fewer Information Errors
Automated QA/QC and structured checking workflows catch data issues earlier, reducing the risk of errors reaching coordination, construction or handover.
Better Coordination Outcomes
Models with complete, consistent and validated data provide a more reliable basis for multidisciplinary coordination, clash detection and construction preparation.
Faster Handover Preparation
Structured asset information workflows and data clean-up reduce the effort required at handover by preparing BIM data for FM use throughout delivery.
Improved Standards Compliance
Regular QA/QC checks help ensure models, parameters and information meet project BIM standards, client requirements and applicable frameworks throughout delivery.
Stronger Data-Driven Decisions
Well-structured, validated BIM data provides a more reliable foundation for analytics, reporting, performance monitoring and project intelligence workflows.
Where this applies.
BIM Coordination & Clash Detection
QA/QC and model validation workflows that improve data quality before models are used for multidisciplinary coordination, clash detection and construction preparation.
Construction BIM & Contractor Delivery
Data validation and model health checks that help contractor BIM teams ensure models are complete, coordinated and compliant before information is issued for construction.
Client & Employer Information Requirements
Structured QA/QC and data validation processes aligned with employer information requirements, BIM execution plans and project information delivery milestones.
Asset Management & FM Handover
Asset information workflows, COBie preparation and data structuring that prepare BIM data for operational use, facilities management and structured project handover.
Standards & Template-Driven Projects
QA/QC and automated checking workflows aligned with strict BIM standards, naming conventions and project templates where consistent data quality is critical across all models.
Multi-Discipline & Multi-Model Projects
Cross-model data validation and health checks for projects involving multiple disciplines and model files where consistent information, naming and data standards need to be maintained.
BIM Data, QA/QC & Model Intelligence FAQs.
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Every engagement is delivered against certified management systems — not just claimed adherence.
Information Management
BIM delivery
Quality Management
Process & delivery
Information Security
Data handling
Environmental
Sustainability