Engineering & Infrastructure

Automate engineering assessments. Capture expert knowledge. Build data-driven infrastructure.

NeoApps.AI transforms complex engineering workflows — design reviews, safety assessments, field inspections, and compliance checks — into structured, AI-powered data that accelerates project delivery and preserves institutional knowledge.

Browse Apps

The challenge in engineering data collection

✕Design reviews and compliance checks done on static PDF forms
✕Expert judgment captured in narrative text that can't be analyzed
✕Field inspection data inconsistent, re-entered manually, hard to validate
✕Engineering knowledge created in design phase, lost by operations
✕No cross-project analytics — issues discovered repeatedly across projects
✕Senior engineers spend hours on documentation, not engineering decisions

Structured assessment → AI post-processing for engineering

Every engineering assessment generates structured, machine-readable data — analyzed by AI immediately and searchable forever.

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STEP 01

Structured Assessment

Engineer completes adaptive assessment form — conditional by structure type, phase, and standard.

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STEP 02

AI Post-Processing

Responses scored against standards, non-compliances flagged, deficiency summary generated.

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STEP 03

Human Review

Lead engineer reviews AI-generated deficiency report, not raw checklists.

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STEP 04

Institutional Memory

All assessments indexed in RAG knowledge base — searchable across projects and years.

Key use cases

Transport Infrastructure — Design Review Automation

Engineering consultancies (SYSTRA, WSP, AECOM) replace static PDF design review checklists with adaptive, AI-scored workflows. AI generates structured deficiency lists and executive summaries.

Conditional assessment logic by structure type (bridge, tunnel, station, trackwork)
Built-in EN, BS, AASHTO compliance scoring rubrics
AI-generated deficiency list with severity classification
Cross-project analytics: recurring non-compliance patterns
Regulatory documentation export for authority submission

Field Inspection & Asset Condition Assessment

Field teams capture structured asset condition data on mobile devices — offline-capable. AI detects anomalies and deteriorating assets, prioritizing maintenance interventions.

Mobile-first, offline-capable inspection workflows
Conditional forms adapt to asset type, age, and criticality
Photo and document capture with GPS tagging
AI anomaly detection: flags deviations from historical norms
Asset lifecycle analytics and predictive maintenance scoring

Safety Audit & Compliance Workflow

Safety officers conduct structured safety audits. AI scores compliance levels, prioritizes findings by risk, and generates audit reports for project management and regulatory bodies.

Safety audit checklists by project phase and site type
Risk scoring: Critical / Major / Minor / Observation
AI-generated audit report with corrective action recommendations
Non-conformance tracking and close-out workflow
Regulatory submission export (PDF + structured data)

Data Intelligence Across Project Lifecycle

Engineering knowledge flows between project phases — design, construction, and operations — with RAG-powered search across all historical assessments and findings.