New Construction Tracking
The Problem
“You can’t manage what you can’t see—construction progress and building risks are fragmented”
Organizations face these key challenges:
Project status lives in emails/spreadsheets, so leadership finds out about delays and safety issues too late
High variance in reporting quality across GCs/sites; risk identification depends on who’s on the job
Teams spend hours reconciling schedules, drawings, RFIs, and field notes into “one version of truth”
Building ops goes reactive after handover: alarms, comfort complaints, and equipment failures drive unplanned work
Impact When Solved
The Shift
Human Does
- •Chase updates from GCs/subs; manually compile progress and risk reports
- •Review drawings/schedules and conduct site walks to spot safety and sequencing conflicts
- •Triage issues via meetings, emails, and spreadsheets; manually prioritize inspections and punch lists
- •Operate buildings with static rules and reactive maintenance after faults occur
Automation
- •Basic dashboards/BI on manually entered data
- •Rule-based alarms in BMS/CMMS with limited context and high false positives
Human Does
- •Set project objectives, risk thresholds, and governance (what must be escalated, when, to whom)
- •Validate/approve AI-flagged issues and recommended mitigations for high-impact decisions
- •Execute field actions (re-sequence work, safety interventions, inspections, repairs) and close the loop
AI Handles
- •Continuously ingest and normalize data from schedules, drawings/BIM, RFIs/submittals, daily logs, photos, and sensors
- •Auto-detect schedule drift, safety conflicts, and quality/compliance risks; generate prioritized risk registers
- •Recommend re-phasing/crew sequencing, safety controls, and inspection focus areas based on learned patterns
- •Predict equipment failures and optimize building setpoints (HVAC/lighting) to reduce energy and comfort issues
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not approve major schedule changes, crew resequencing, or recovery plans without a project manager or construction manager decision. [S1]
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in New Construction Tracking implementations:
Key Players
Companies actively working on New Construction Tracking solutions:
+10 more companies(sign up to see all)Real-World Use Cases
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