Verified Outcomes · Real Factories · Measurable Impact

Real results from
real factories

Every number on this page comes from a live deployment. Measurable, verified outcomes from factories that trusted CountAI to solve problems their teams couldn't crack alone.

~80%
Defect Losses Cut · Aarti International
1.5% → 0.2%
Knitting Waste · Best Color
90 Days
Full Rollout
Textile & Apparel

South Asian Textile Group

One of South Asia's largest vertically integrated textile conglomerates, operating 200+ circular knitting machines across 4 plants, producing knitted fabrics for global fashion and sportswear brands.

The Challenge

With circular knitting machines running across four plants, manual inspection was failing to keep pace. Human inspectors were missing 15–20% of fabric defects at production speed.

  • Customer complaints rising quarter-over-quarter
  • Export orders at risk due to quality inconsistency
  • No standardised grading system across plants
  • Inspector fatigue on 12-hour shifts compounding miss rates
The Solution

CountAI deployed Knit-I across all four plants — the same system running in 30+ factories in 7 countries.

  • High-speed cameras installed on every machine
  • Intel-based edge compute for on-premise processing
  • Custom AI models trained for 150+ fabric types
  • Automated fabric grading reports generated per roll
  • Real-time alerts and machine halt capability
The Results
  • Sharp drop in defects reaching customers — caught live, at the machine
  • Fabric grading reports auto-generated for every roll
  • Inspection team redeployed to higher-value QC roles
  • Export order rejection rate dropped to near zero
  • Consistent quality across all 4 plants for the first time
24/7
Live Inspection
200+
Machines Covered
150+
Fabric Types
4
Plants Deployed
“The AI catches what our best inspectors couldn't — consistently, at full speed, 24/7.”
— Head of Quality, South Asian Textile Group
Deployment Timeline
1
Pilot
2 weeks — Single machine proof of concept
2
Plant 1 Rollout
6 weeks — Full first plant deployment
3
All 4 Plants
90 days — Complete multi-site rollout
Tyre & Rubber

Major Tyre Manufacturer

India's largest tyre manufacturer, operating high-volume Tyre Building Machine (TBM) bays with demanding production targets across multiple shifts.

The Challenge

TBM bays were running at unknown true efficiency. Supervisors had no visibility into how time was being spent — blocked, starved, idle, or productive.

  • Production targets consistently missed by 5–8%
  • No data on blocked/starved/idle time per operator
  • Root causes of downtime invisible to management
  • Subjective shift reports with no granular time data
The Solution

CountAI deployed a Man-Machine IoT system using existing CCTV cameras — no new hardware required on the production floor.

  • AI classifies every second of every operator shift
  • Four activity states tracked: S1 (productive), S2 (blocked), S3 (starved), S4 (idle)
  • Real-time dashboards for supervisors and plant managers
  • Automated shift-end reports with time breakdowns
The Results
  • 15–30 minutes recovered per bay per shift
  • Root causes identified: material delays, tool changeover gaps
  • 1–3% output uplift per bay measured
  • Data-driven shift scheduling implemented
  • Plant-wide rollout approved after PoC results
15-30
Minutes Recovered / Bay / Shift
5-8%
Production Gap Closed
1-3%
Output Uplift Per Bay
0
New Hardware Required
“We were sceptical about a 6-week trial. The data spoke for itself — we saw problems we didn't know existed.”
— Plant Manager, Major Tyre Manufacturer
Deployment Timeline
1
Proof of concept
6 weeks — on the customer’s own bays
2
Results Presentation
Data-driven ROI review with leadership
3
Plant-Wide Rollout
Decision to deploy across all TBM bays

See what CountAI can do
for your factory

Every deployment starts on your own machines. We bring the cameras, compute and AI. You bring the problem. Results speak for themselves.

Intel Edge AI Award 2026 Proven in 30+ factories On-Premise Deployment Results in Weeks
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