Today
Sampling finds problems late
- Inspection samples are chosen without a job-level risk ranking.
- Documentation is checked mainly for completeness.
- Complaints or delayed findings often trigger investigation.
You cannot inspect every job.You can rank which ones matter first.
Retrofit programmes produce more evidence packs than inspection teams can visit. INSUS reads the documentation trail, flags inconsistencies and ranks jobs by the likelihood that a physical inspection would find a remediation-grade defect. Inspectors still decide what to visit and what they find.
01
A complete pack is not a clean install.
02
Inspection capacity needs prioritisation.
03
A low score is not a compliance certificate.
The problem
A complete evidence packdoes not guarantee a good installation.
Retrofit quality assurance leans on assessments, designs, evidence packs and installation records. At programme scale, physical inspection cannot cover every property. The hard part is not only checking that documents exist, but spotting which records carry signals that warrant a closer look.
01Assessment
02Design
03Installation
04Evidence pack
05Sign-off
- 01Assessment
- 02Design
- 03Installation
- 04Evidence pack
- 05Sign-off
The shift
From random samplingto risk-ranked inspection.
Inspectors stay responsible for the physical finding. What changes is whether limited visits are ordered by document risk signals across jobs, installers and property types.
With INSUS
Inspection effort follows evidence of risk
- Jobs are ranked by modelled inspection risk with contributing factors.
- Documents are checked against each other for consistency.
- New inspection outcomes feed back to improve the ranking.
How it works
From evidence packsto a ranked inspection list.
Delivered through ExpertFlow AI as document intelligence over retrofit records. It ranks where to inspect. It does not certify compliance, clear payments or replace the inspector.
Connect
Bring the job records together
Read-only links to assessments, designs, ventilation records, product details, installation photos and metadata, scheme records, installer and assessor history, property data and historical inspection outcomes.
Understand
Check documents for consistency
Compare documents within each job for agreement between system, property, ventilation and installation evidence. Surface patterns across installers, assessors and coordinators where identifiers exist.
Predict
Rank inspection risk
Estimate the likelihood that a physical inspection would find a remediation-grade defect, with contributing factors so teams can see why a job was prioritised.
Advise
Focus limited inspection capacity
Hand inspectors a prioritised list with job-level concerns and portfolio views by installer, region, property type or measure. No automatic fail, clear or enforcement action.
Verify
Learn from inspection outcomes
Each inspection result becomes a new label. Performance is compared with the existing sampling approach using hit rate and related triage metrics.
Getting started
Start with a closedhistorical cohort.
For organisations that already hold large volumes of retrofit job records and historical inspection outcomes. Delivered through ExpertFlow AI as document intelligence for inspection triage. Expert Services can help with discovery and back-test design. The model supports prioritisation. It does not certify an installation.
- What we need. Evidence packs and lodgement records, installer and assessor identifiers, relevant property information and historical inspection outcomes for training and validation.
- What you see first. A retrospective risk ranking of known jobs, consistency flags and a hit-rate comparison against the sampling method already in use.
- How it grows. After a successful back-test, ranking can inform live inspection prioritisation as new outcomes refine the model.
Related for insulation
Other insulationstarting points
Retrofit triage sits beside melting energy and declared lambda margin on the same insulation business.
- 01Mineral Wool Melting & Curing Energy OptimizationRecommend furnace and curing-oven settings from plant energy and process history inside melt and cure constraints.
- 02Insulation Declared Lambda OptimizationModel thermal-conductivity variation and review declared lambda margin from process and lab history.
- 03Insulation industryThe wider picture for mineral wool melting energy, declared lambda and retrofit documentation.
Questions retrofit quality teams ask us
Programmes generate more jobs than inspectors can visit. This use case ranks jobs by modelled inspection risk from documentation and historical outcomes so limited capacity focuses where remediation is more likely.
Evidence packs and lodgement records, installer and assessor identifiers, relevant property information and historical inspection outcomes for training and validation.
No. It analyses digital records and prioritises visits. A low risk score is not a finding that an installation is compliant, and it has no authority over certification, payment or enforcement.
No. The use case works from existing digital documentation, property data and inspection records. It can only assess what has been documented.
No. Inspectors remain responsible for physical findings. A model score should not independently clear, fail or penalise an installer or property.
Start with a retrospective back-test on jobs with known inspection outcomes, using temporal hold-out and comparing hit rate with the existing sampling method.
Through ExpertFlow AI as document intelligence for inspection triage. Expert Services can support discovery, data readiness and back-test design against your own cohort.
Insulation · Retrofit quality assurance
You cannot inspect everything. You can choose better.
If you hold job records and historical inspection outcomes, a retrospective back-test can show whether risk-ranked inspection would outperform the sampling method you use today, before any live deployment.