Industrial AI solution

Digital Twin AI For EPC & Infrastructure

Live project twins that combine BIM, schedule and drone data with AI to predict slip, detect clashes and protect margin.

Plan the use case Explore ROI tools

Digital twin AI for an EPC construction project

Acceptance before scale

Baseline, representative test set, failure conditions and a named human owner are defined before production approval.

Direct answer

NeoBram delivers AI digital twins for EPC projects that fuse BIM, Primavera P6, drone progress data and field reports - predicting schedule slip, detecting design clashes early and giving leadership a single source of truth on project health.

Private deployment available

Why evaluate it

EPC Projects Lose Margin In the Gap Between Plan and Site.

The decision is whether this capability improves a defined workflow safely not whether an AI demo looks impressive.

A digital twin unifies BIM, Primavera P6, drone / 360-camera capture and field reports. AI on top predicts slip, surfaces clashes weeks before they bite, and benchmarks productivity against plan.

We deliver twins that integrate with your existing CDE (Aconex, ProjectWise, BIM 360) - not a new platform to learn. Project controls and superintendents get answers in their existing tools.

Uncited universal benchmarks from the legacy page were withheld. Define the baseline and acceptance threshold from customer evidence or a reviewable primary source.

Candidate capabilities

What a production solution may need to do.

Each capability is validated against representative data and the customer's workflow. Product or model names describe possible components, not partnerships, certifications or guaranteed compatibility.

Live project twin

Federated 4D / 5D twin that links BIM elements to schedule activities and actual progress from drone capture - updated weekly or daily.

BIM-to-P6 element linking
Drone-derived progress per zone, level, system
Plan vs actual visualisation in 3D
Earned value rolled up to leadership dashboards

AI clash & constructability

ML-augmented clash detection that ranks issues by site impact and constructability - cuts the false-positive noise that drowns reviewers.

Severity ranking, not just count
Constructability checks (access, lift paths, sequencing)
Auto-assigned to discipline owner
Weekly closure rate dashboard

Schedule slip prediction

A candidate capability to test against a documented baseline, representative scenarios and agreed human-review workflow.

Per-activity slip probability
Productivity benchmarks by trade and project type
Weather, permit and material risk overlays
Recommended mitigations with cost / schedule impact

Field-to-office reconciliation

Auto-reconciles superintendent reports, RFIs, NCRs and drone capture against plan - replaces the Monday morning manual report pull.

RFI / NCR theme clustering
Quantity reconciliation against pay items
Photo-evidence linked to schedule activities
Single weekly leadership digest

Architecture context

Select components after the boundary and test are clear.

The list is a design vocabulary. Final selection depends on licences, data location, latency, security, existing systems and customer approval.

Source systems

Autodesk Construction Cloud / BIM 360
Models and drawings
Bentley ProjectWise
Engineering CDE
Aconex / Procore
Field collaboration
Oracle Primavera P6
Schedule

Capture & ingest

Drone photogrammetry (DJI, Skydio)
Site capture
Matterport / Navvis
Indoor 360
Reality capture (RealityCapture, ContextCapture)
Point clouds

AI & analytics

Computer vision (YOLO, SAM)
Progress quantification
PyTorch
Schedule risk models
Graph neural networks
Dependency analysis

Twin & viz

NVIDIA Omniverse
Federated 3D twin
Cesium
Geospatial twin
Forge Viewer
BIM viewing

Planning ranges

A standard path from decision to operation.

Discovery and qualification

1-2 weeks

Named workflow, owner, baseline, risks and go/no-go questions.

Readiness assessment

2-4 weeks

Data, integration, security, value and operating-readiness findings.

Technical proof of value

4-6 weeks

A bounded test on representative data with documented limitations.

Production pilot

8-12 weeks

One controlled workflow, integrated and evaluated with real users.

Enterprise or multi-site rollout

3-6+ months

Phased scale-out, monitoring, support and change management.

AI capability or CoE programme

3-6+ months

Governance, delivery methods, reusable assets and team enablement.

These are planning ranges, not guarantees. Readiness, validation, hardware, integration, access and change management affect the schedule.

Production safeguards

Private deployment is one control, not the whole control system.

Data boundary

Select offline, edge, on-premises or private-cloud deployment from the real operating constraints.
Document data flows, storage, deletion, backups and support access before production.
The customer approves every interface and any permitted external connection.

Model and application controls

Evaluate representative cases, uncertainty and harmful failure modes before use.
Use suitable access control, input handling and output guardrails for the selected risk.
Treat grounding and citations as testable behaviours, not as a promise of perfect answers.

Traceability and operation

Define identity, roles, logs, monitoring, updates, backup and incident handling.
Keep the evidence needed to investigate outputs and reproduce important decisions.
Assign a named business and technical owner for production operation.

Human authority

Domain, quality, safety and regulatory owners retain decision authority.
Compliance depends on the implemented system and the customer's validated controls.
Escalation and safe fallback are part of the acceptance criteria.

Limitations to plan for

Performance can change with data quality, equipment, process, product mix, documents, users or operating conditions. Third-party model and software licences still apply. AI output does not replace the responsible engineer, operator, quality owner, safety professional, legal adviser or regulator.

Buyer questions

Direct answers before you plan a pilot.

Do we need a fully federated BIM to start?+

This legacy draft included a quantitative benchmark that has not been published with a reviewable source or customer evidence. NeoBram now treats it as an open validation question and defines the baseline, test method, acceptance threshold and limitations during discovery.

How is this different from 4D BIM tools we already have?+

Traditional 4D BIM is a static visualisation. Our twin adds two things: continuous reconciliation with actuals (drone, field data) and AI prediction on slip, clash severity and productivity. It becomes the operational source of truth, not just a presentation tool.

What drones and capture cadence do you recommend?+

For typical industrial / infrastructure sites, weekly drone capture with DJI Matrice 30T or Skydio X10 is the sweet spot. Indoor progress uses Matterport or Navvis monthly. We process the imagery into orthomosaics, point clouds and AI-quantified progress automatically.

Does it integrate with our existing CDE?+

Yes. Native integrations with Autodesk Construction Cloud / BIM 360, Bentley ProjectWise, Aconex and Procore. Project teams continue using their CDE; the twin enriches it.

How long to first value?+

A focused production pilot is commonly planned over 8 12 weeks after scope, representative data, owners and acceptance tests are ready. Discovery or a technical proof of value may be shorter; integration, validation, hardware, site access and change management can extend the plan. This is a planning range, not a delivery guarantee.

Who owns the data and models?+

You do. The twin runs in your cloud tenant. Models, code and the data pipeline are deliverables, fully transferable. No vendor lock-in.

Bring one workflow

Define the evidence, boundary and acceptance test together.

Your team supplies process authority. NeoBram supplies AI architecture, engineering, evaluation and operating handover.

Plan the first project