Fiber construction close-out packages bundle hundreds of files per site: test workbooks, OSP drawings, OTDR traces and photo evidence. Reviewing them by hand is slow, and sampling misses defects. NetSingularity COP Analysis reads the entire package against the customer's own QA checklist: every reading, every photo, every drawing, and flags exactly what a human still needs to decide.
The Challenges
Before a carrier accepts a finished build, and releases payment, the contractor must prove the work: fiber design sheets, as-built drawings, power meter readings, OTDR traces, and photo evidence for every unit and port. For a single 30-unit MDU, that is hundreds of artifacts. In practice, nobody reads them all.
A site folder spans 13 expected sub-folders: Excel design workbooks, CAD-derived PDF drawings, OTDR trace files (PDF and RAW), power meter reports, and hundreds of field photos. Formats vary by crew and by site.
Verifying one site means cross-referencing design revisions, reading 30 meter LCD photos, checking 60 OTDR readings against a loss threshold, and matching every splitter port to a photo. Reviewers sample, and sampling misses defects.
30 photos for 30 ports proves nothing: photos can be duplicated, illegible, or show no light. Test reports number fibres positionally, not by network fibre number. Naive checks pass packages that should fail.
A defect the carrier's QA finds after submission bounces the whole package: re-truck-roll, re-test, resubmit. Late-found defects delay acceptance, and payment, by weeks per site.
The Approach
NetSingularity connects straight to the contractor's document store, ingests each site folder as-is, and runs a dozen automated checks, 300+ individual verifications per site, that mirror the carrier's own QA rules, combining deterministic file analysis with computer vision, and routing anything uncertain to a human instead of guessing.
Sites import directly from Dropbox or OneDrive. A file and data audit maps what is present against the 13 expected folders, so missing evidence is visible before any analysis runs.
Pre/Post-FDS cross-reference, power meter/OPM, OSP drawing versus as-built, photo evidence (six sub-analyses), OTDR trace analysis, and conditional Tier-2 testing, with each rule quoted from the customer's checklist, verbatim.
Vision reads meter LCDs and detects ruby light, but OCR is never trusted to condemn a reading; uncertain items go to a manual-read queue, and threshold questions become explicit customer decisions.
Results in the Field
A 7-building, 30-unit MDU with 30 assigned fibres. NetSingularity analyzed the full package and produced a per-checklist verdict, passing what is proven, failing what is defective, and queueing what needs a human.
The latest Post-FDS revision was auto-selected from competing versions, and nine identity fields (CO, FSA, fibre range, buildings, unit counts, FIP) were cross-referenced against Pre-FDS. All matched; the 80% fibre-in-place gate cleared.
In-suite (30/30) and feeder (30/30) OPM readings confirmed within the 0.01–1.49 dB acceptance window at both wavelengths, with the report's positional fibre index correctly mapped to real network fibre numbers.
Predesign and as-built drawings both present; the as-built NAP table (9 access points with their fibre assignments and unit mappings) agrees with Post-FDS field by field, rendered as a visual feeder diagram.
Ruby-light analysis resolved every port in the assigned fibre range to a photo showing the glow and a legible tag (90–100% confidence), because a photo count matching the port count is not proof.
Vision OCR read both wavelength values off 27 handheld-meter LCD photos and confirmed them in range. Three unreadable or truncated displays went to the manual-read queue, never auto-failed on OCR alone.
OTDR trace analysis (30 fibres × 2 wavelengths) confirmed 55/60 readings under the 0.333 dB loss threshold, and isolated one fibre at roughly twice the allowed loss (0.695 dB against the 0.333 dB limit), splice by splice, with the failing events pinpointed by distance, and flagged for repair before the package ever reached the carrier.
Inside the Platform
Six checklist areas, with photo evidence alone spanning six further sub-analyses (OPM test, ruby light, NAP, splice/FOSC, POE, MER/SER). Every module shows the customer's original checklist wording, what the engine checks, what passes, and the full evidence trail, down to each photo, reading and drawing, with per-item confidence.
Folder-by-folder presence audit against the 13 expected COP folders, synced live from Dropbox or OneDrive.
Latest-revision selection, identity cross-reference, unit and building counts, and the fibre-in-place gate.
In-suite and feeder report parsing; every reading checked against 0.01–1.49 dB at both wavelengths.
Predesign and as-built presence, NAP-table agreement with Post-FDS, inline drawing preview.
OPM meter reads, ruby-light port confirmation, NAP, splice, POE and MER/SER photo evidence.
Trace parsing per fibre per wavelength, in-scope splice-loss checks, RAW and PDF pairing, event-level detail.
The Impact
Package review
Review that took a reviewer the better part of a day per site runs automatically; humans touch only the queued exceptions.
Acceptance cycle
Defects surface before submission, not in the carrier's QA, avoiding the reject-refix-resubmit cycle that stalls acceptance and payment.
Evidence coverage
Every unit, port, fibre and wavelength is checked on every site, coverage a manual reviewer cannot deliver at any headcount.
Each engine quotes the carrier's checklist wording and shows exactly what was checked and what passes: QA the customer can audit, not a black box.
OCR and light detection do the heavy lifting, but uncertain reads are queued for a human, so the platform never fails a unit on a low-confidence read.
Ambiguities, like whether a loss threshold applies to in-scope splices or total loss, become tracked decision items routed to the customer, instead of silent assumptions.
Per-site readiness reports with downloadable source files and PDF export give the carrier proof of work, and the contractor a faster path to acceptance.
The Business Case
Construction QA failures are not an abstract risk; the industry has measured them. These published benchmarks frame what a missed defect, a bounced package, or a delayed acceptance actually costs, and what automating close-out review is worth.
of total construction project cost is typically consumed by rework, and inaccurate data alone causes 14–22% of it.
PlanRadar / academic rework studies
of fiber deployment cost is labor, so every avoidable re-visit burns the most expensive line item on the build.
Fiber Broadband Association / Cartesian
direct cost of a single field truck roll; up to roughly $1,000 all-in once indirect costs are counted.
Field-service industry estimates
average construction payment cycle, and close-out acceptance is the gate that starts the clock on final payment.
Rabbet Construction Payments Report
Every input below is adjustable to your rates and volumes; the structure is what matters.
| Cost lever | Manual QA today | With NetSingularity | Impact per site |
|---|---|---|---|
| QA review labor | A true full review, covering 30 meter LCD photos, 30 ruby-light ports, 60 OTDR readings, and workbook and drawing cross-checks across 400+ files, takes 1.5–2 days. In practice teams sample it in 2–3 hours and accept the blind spots. | Full-coverage analysis runs in minutes; a reviewer spends ~30–45 minutes on the queued exceptions only. | ~95% less review effort, at 100% coverage instead of a sample. At a loaded QA rate of $75–100/hr, that is $850–$1,500 of full-review labor per site, delivered for under an hour of human time. |
| Defect escape → bounced package | A defect the carrier finds post-submission triggers re-mobilization, re-test and resubmission: $800–$1,500 per bounce in crew time and truck rolls, plus a 1–3 week resubmission cycle. | Defects, like the over-threshold splice on the featured site, surface before submission, fixed inside the normal work flow. | Bounce avoided; the featured site alone represents one prevented rejection cycle. |
| Payment timing | Final payment is gated on accepted close-out. Every week a package sits in reject-refix-resubmit costs ~$190 per $100K of invoice value in carrying cost (at 10% financing), on top of the ~90-day industry payment cycle. | First-pass acceptance pulls invoicing forward 1–3 weeks per affected site, with an evidence trail the carrier can audit. | Faster, defensible cash flow, and fewer disputes, because every claim links to its source file. |
Illustrative annual impact for a contractor closing out 100 comparable MDU sites, assuming a 20% historical rejection rate improved to 5%.
| Value stream | Basis | Annual impact |
|---|---|---|
| QA labor redeployed: reviewers move from page-turning to exception handling | 100 sites × ~11–15 h of full-review-equivalent labor × $75–100/hr loaded | ~$85K–$150K |
| Rejection cycles avoided: 15 fewer bounced packages (20% → 5%) | 15 × $800–$1,500 re-mobilization and re-test | ~$12K–$23K |
| Payment acceleration: 15 sites paid 1–3 weeks sooner | Carrying cost at ~$190/wk per $100K invoice | Weeks of cash flow pulled forward, fewer disputed invoices |
| Risk not priced above: defects that would otherwise ship, including warranty exposure, carrier scorecard damage, and rework that industry-wide consumes 4–10% of project cost | One prevented systemic defect pattern can exceed every line above | Downside protection |
Six operational metrics, measurable from the platform itself, before and after, per site and per crew.
Share of packages accepted by the carrier without a rejection cycle, the single KPI that drives cash flow.
Defects found by the carrier after submission. Every escape on the featured site class is now caught pre-submission.
From package-complete to QA verdict, including human review of queued exceptions.
Every unit, port, fibre and wavelength verified on every site, versus the 10–20% a sampling review actually inspects.
Share of items needing human eyes (3 of 30 meter photos on the featured site), trending down as vision models learn each meter type.
Invoice-ready date pulled forward on sites that would otherwise bounce, against a ~90-day industry payment cycle.
Benchmark sources: rework at 4–10% of project cost and inaccurate data causing 14–22% of rework, from PlanRadar, Cost of Rework in Construction (2025); labor at 60–80% of fiber deployment cost, from FBA / Cartesian Fiber Deployment Cost Annual Report; truck-roll cost estimates of $150–$500 direct and ~$1,000 all-in, from VSight field-service glossary; ~90-day average construction payment cycle, from Rabbet 2024, via BuildLedger. Per-site and portfolio figures are illustrative models built on these benchmarks and the featured site's measured workload; replace rates and volumes with your own to localize.
The Platform
A web platform that turns raw construction close-out folders into per-site QA readiness reports, with checklist engines, computer vision, decision workflow and full evidence drill-down in one place.
Dropbox
Site folder import & sync
OneDrive
Site folder import & sync
Excel / PDF / CAD
FDS workbooks & drawings
OTDR .sor + field photos
RAW traces & evidence
The Path Forward
Roll the full battery of automated checks across the construction portfolio as packages land.
Resolve open threshold decisions with the carrier so verdicts finalize without ambiguity.
Extend the remaining photo sub-analyses (NAP, splice, POE, MER/SER) to full automation.
Turn recurring defect patterns into crew-level feedback, catching issues before packages are even assembled.
If your teams are sampling their way through construction QA, or your customer keeps finding what your reviewers missed, NetSingularity will read every file and show you, site by site.
A network of hundreds of thousands of sites generating ~1.25 crore alarms a day, handled by static correlation rules and manual RCA. Six coordinated AI capabilities turned that flood into unique actionable incidents, without a single byte leaving the operator's estate.
Thousands of change requests a month across hundreds of change categories, assessed by checklist and delivered by hand. Seven coordinated flows turn each CR into a risk-scored, simulation-backed, auditable operational outcome.
O-RAN gives operators vendor choice, and with it more moving parts to coordinate on every site turn-up. One automation layer now carries planning data, field capture, provisioning, configuration and verification end to end.
Case study based on a live site deployment. Customer identity and site details anonymized. Time-savings figures are engagement estimates based on the workload automated per site; they will be refreshed with measured numbers as the deployment scales across the site portfolio.
