Both are possible. For most integrations, DAQS builds and maintains the rules in collaboration with the platform team — you define your data specification, DAQS translates it into validation logic applied upstream. A self-service rule editor for direct configuration is in development.
Solutions — Platform Teams & CTOs
Your platform is only
as good as
the data it receives.
AI engines, construction operating systems, planning tools, and ERP all depend on model data. That data comes from BIM. If it's incomplete, inconsistent, or unvalidated, everything built on top of it inherits the problem. DAQS is the layer that fixes that at the source.
Without validated input
AI models trained on bad data produce bad outputs. Planning tools optimise the wrong quantities. ERP receives incomplete specifications. Digital twins diverge from reality from day one.
DAQS validates at the source
With DAQS upstream
Every downstream system receives data that has been checked against governance rules, structured to specification, and validated before it leaves the model. Your platform's reliability is no longer contingent on how well someone filled in BIM.
The problem
Construction data is abundant. Trustworthy construction data is not.
The construction industry generates enormous volumes of model data. The problem isn't quantity — it's reliability. Every platform team building on BIM data eventually hits the same ceiling.
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Inconsistency across models and projects
Different engineers, different companies, different conventions. The same element type is named, structured, and attributed differently on every project. Normalising this downstream is expensive and never complete.
⊘
Missing and incomplete data
95% of construction data is never used — not because it isn't needed, but because it was never captured correctly. Fields are empty. Properties are missing. The model exists but the information doesn't.
⧗
Validation happens too late
By the time data reaches a platform, it has passed through export, conversion, and transfer. Errors introduced anywhere in that chain are invisible. Cleaning data after ingestion is reactive, costly, and never upstream enough.
What DAQS is
The intelligence layer between models and systems.
DAQS sits between BIM models and the operational systems that depend on them. It validates data in Revit — at the source, before any export — and structures it into the exact format each downstream system requires.
For platform teams, this means the data contract between models and your system is enforceable. Rules defined in DAQS are applied to every engineer, on every model, before data leaves the authoring environment. What reaches your platform has already been checked.
"No automation without data quality."
The reverse is equally true: with validated data as input, automation becomes reliable. The quality of what DAQS delivers upstream directly determines what your platform can do downstream.
Where it applies
What platform teams use DAQS for
The same validation and structuring layer applies wherever construction model data needs to be reliable enough to act on.
AI & machine learning
Clean training data and reliable inference input
AI models are only as reliable as the data they're trained and run on. DAQS ensures model data is consistent, complete, and governed before it enters any AI pipeline. The same rules applied to training data are applied to production input — so inference results reflect what was actually specified, not what happened to be in the model.
Construction OS / Data platform
A validated, governed data feed from every project
Construction operating systems require a continuous, reliable feed of model data across all projects and disciplines. DAQS provides that feed with governance rules enforced upstream. The data entering your platform has been validated against your specification, structured to your schema, and delivered directly — not scraped, converted, or manually prepared.
Digital twin
A source layer that matches design intent
A digital twin is only as accurate as the model it's built from. When engineers validate their models against governance rules before publication, the twin starts from a position of data integrity — not from whatever state the model happened to be in at handover. DAQS makes the as-designed state explicit and verifiable.
Supply chain & ERP
Structured element data, ready for operational systems
ERP and supply chain systems require structured, consistent data. DAQS Elements generates production-ready output files from validated IFC, mapped to the exact schema each system expects. The Validate → Transform → Connect pipeline is already live for door ordering and expanding to every element type that flows from model to production.
The shift
From data cleaning to data governance
The difference between cleaning data downstream and governing it upstream isn't just efficiency. It's whether your platform's reliability is structural or contingent.
Before
Data quality is a platform problem. Ingestion pipelines clean, normalise, and validate after the fact. Errors caught late, fixed expensively, never fully resolved.
↓
After
Data quality is enforced at the source, in Revit, before any export. Your platform receives data that already meets its specification. Ingestion pipelines process, not repair.
Before
Each project delivers data in a different structure. Normalisation logic accumulates indefinitely. Scale creates more variation, not less.
↓
After
Governance rules are defined once and applied across every project, every engineer, every discipline. Your schema is enforced upstream. Consistency is structural.
Before
Platform reliability depends on how carefully individual engineers filled in their models. You have no visibility into that process and no leverage over it.
↓
After
Your data specification is part of the engineering workflow. Engineers see validation results in Revit. Compliance is visible, measurable, and continuous — not assumed at handover.
Integration
How DAQS connects to your stack
How projects typically operate today
Models are delivered. BIM coordinators validate them in Solibri or similar tools. Issues are returned as BCFs. Designers correct the model, export again, and deliver a new version. This validation and correction cycle repeats at every milestone, across every discipline.
DAQS changes where validation happens
Is designed to sit upstream of your existing systems — not to replace them. The interface to your platform is a structured, validated data feed. How that feed connects depends on what you're building.
⬡
The rework cycle
Without upstream validation, every issue found in a platform triggers another correction cycle in the authoring model. DAQS validates data before export, reducing delays and repeated exchanges between design teams and platform owners.
⇄
Schema mapped to your specification
DAQS transforms validated model data into the exact structure your system expects. You define the schema once. DAQS maintains the mapping and enforces it upstream on every model.
→
Direct delivery to operational systems
Output is delivered directly to your platform — order systems, ERP, planning tools, AI pipelines, or construction OS. Integration depth is defined during onboarding and can be extended over time.
⊞
Multiple source formats
DAQS works with Revit models, IFC exports, and other formats as the authoring landscape evolves. The extraction method differs per format — the governance layer and the output specification remain consistent.
The data quality problem in construction is not a modelling problem. Engineers are building complex models under time pressure. The issue is that quality was never part of the authoring workflow — it was always a downstream check.
DAQS moves the check upstream, distributes it across every engineer, and makes the results visible to whoever is responsible for data governance. That shift doesn't require changing your platform. It changes what your platform receives.
95%
of construction data is never used
41%
of decisions negatively affected by bad data
Frequently asked
Questions from platform teams
Can we define the validation rules, or does DAQS set them?
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What does the data contract between DAQS and our system look like?
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DAQS delivers structured output — either as a formatted file (JSON, CSV, or domain-specific format) or via direct API connection to your system. The schema is defined upfront based on your requirements. We start with what your system already expects, not a new standard you have to adapt to.
How does DAQS handle multiple contractors contributing to the same platform feed?
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Each contractor runs DAQS against their own models independently. Governance rules are defined once and applied consistently regardless of which contractor produced the data. From your platform's perspective, the output is consistent across all contributing projects — variation in contractor workflow doesn't propagate downstream.
Does this require changes to how contractors work?
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Minimal. DAQS Assist runs inside Revit — engineers don't change their modelling workflow, they gain visibility into how their data measures against the specification. The BIM coordinator defines the rules and sees compliance status in the dashboard. From a platform perspective, the change is upstream and largely transparent to the engineering teams.
Where does DAQS fit relative to our existing data ingestion pipeline?
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DAQS sits upstream of your ingestion layer. Rather than cleaning and normalising on ingest, your pipeline receives data that has already been validated and structured. This doesn't eliminate your ingestion logic — but it changes what that logic has to handle. Most teams find the downstream complexity reduces significantly once the upstream is governed.