Cognecto Customers UPRRDA
Government · Road Construction

UPRRDA — evidence-based
quality monitoring at scale.

NH Corridor · Package 6152 · Uttar Pradesh, India

How UPRRDA's adoption of Cognecto's Vision AI monitoring transformed quality assurance on Package 6152 — delivering 95/100 quality, 4× operational transparency, and a model for evidence-based public infrastructure governance.

UPRRDA Package 6152 road construction
95/100
Quality score
Transparency
9.23 km
BC+CC documented
Customer
Uttar Pradesh Rural Road Development Authority (UPRRDA)
Sector
Government · Rural Road Construction
Location
Uttar Pradesh, India · NH Corridor Package 6152
Scope
9.23 km BC + CC road · Pre to post-construction
Cognecto modules
Boson + Photon + Cortex · Highway solution
Go-live
2024 · 7-day deployment

Quality assurance built on tally sheets and trust.

UPRRDA's mandate covers thousands of kilometres of rural road construction across Uttar Pradesh under the PMGSY programme — work delivered by hundreds of contractors and inspected by a finite team of site engineers. The system that scaled this work was paper-based: manual tally sheets for roller passes, subjective visual inspections for cement spread quality, and post-construction certification that could not retrospectively verify what happened during layer construction.

By the time a quality defect surfaced — typically through pavement failure 12–18 months after handover — the contractor had moved on, the responsible inspector had rotated, and the evidence chain to assign accountability did not exist. Disputes were unresolvable. Rework costs were borne by the public exchequer. And the underlying quality control gap stayed in place because no alternative system had been built for the scale of work involved.

  • Manual roller pass tallying — no chainage-level verification, no audit evidence
  • Subjective spread quality assessment — disputes between contractor and inspector
  • No baseline survey methodology — pre-construction conditions not documented
  • Post-construction defects untraceable to construction-phase decisions
  • Inspector-to-package ratio made comprehensive coverage impossible

End-to-end monitoring across all three construction phases.

Cognecto deployed its full Highway solution stack across Package 6152 — covering pre-construction baseline survey, real-time construction monitoring, and post-construction condition assessment. The deployment used existing site cameras and standard GPS-enabled telematics on equipment, with the Cortex knowledge graph linking every observation to the BOQ line item it verified.

Pre-Construction Survey
AI-measured road width profiling (±5cm precision), obstruction detection, OMMAS-compatible KML output for baseline documentation.
Roller Pass Verification
Every compaction pass GPS-verified per chainage, per lane, per layer — validated against PMGSY FDR sequence requirements.
Cement Spread AI
Photon vision models detect spread thickness anomalies and coverage gaps in real time — flagged before the roller arrives.
PPE & Safety Monitoring
Vision AI on entry points verifies helmet, vest, and boot compliance for every contractor worker — 25% compliance improvement.
BOQ-Linked Progress
Every verified layer automatically clears the matching BOQ line in Cortex — variances flagged before next phase begins.
Post-Construction Scan
Defect classification, edge line continuity (98.4% verified on 18.18 km), and width compliance assessment for handover baseline.

Real-time AI alerts enabled same-day corrective action — Package 6152 became a working example of how technology can redefine quality control in public infrastructure delivery.

A new standard for public infrastructure governance.

The outcome on Package 6152 was measurable across quality, transparency, and accountability dimensions — but the larger impact was structural. UPRRDA now has a documented methodology for evidence-based monitoring that can scale across every package, every district, and every state RRDA. The model became a reference point for what AI-led quality assurance looks like at PMGSY scale.

95/100
Overall quality rating — no major or moderate defects detected
Operational transparency vs traditional monitoring
40%
Rework cost reduction — same-day AI corrective action
60%
Inspection time saved vs traditional manual methods
98.4%
Edge line continuity verified on 18.18 km marking
100%
Geo-tagged evidence on every compaction pass
"Cognecto has set a benchmark for evidence-based quality monitoring in road construction. The adoption of Cognecto's Vision AI Technology marks a significant step forward for UPRRDA in building world-class rural infrastructure. Evidence-based monitoring has not only improved quality assurance but also demonstrated how technology can redefine public infrastructure governance."
Shri Akhand Pratap Singh, IAS
CEO, UPRRDA · Uttar Pradesh Rural Road Development Authority