Customer Stories · Proven in Production

Industrial intelligence operating every day.

Multi-year deployments across manufacturing plants, global data centres, network infrastructure and supplier ecosystems—not laboratory demonstrations.

Named deployments · Daily operational use
5 years

FaciliVISS in Nokia daily operations

3 years

Qualitiviss at Wheels India

10+ plants

Wheels India quality footprint

4 plants

DatVision AI at Ashok Leyland

20+ rollouts

DatVision AI across customers

100+

Tier-1 and Tier-2 suppliers

Deployment Evidence

Built around operations that cannot stop.

Each story shows the deployed scope and duration. Commercial outcomes are deliberately not invented; the evidence shown here is operational.

01
FaciliVISS · Facility & utility operations

Nokia

Five years in daily operations across mission-critical facilities.

FaciliVISS supports two global data centres, one network centre and an electronics manufacturing facility at Nokia. The platform brings recurring facility and utility intelligence into the operating rhythm without replacing the systems already in place.

2 global data centres
1 network centre
1 electronics manufacturing facility
Five years of daily operational use
What this demonstrates

Long-duration operation across different facility types, from digital infrastructure to manufacturing.

02
Qualitiviss + QAI · Quality operations

Wheels India

A three-year quality foundation now extended with QAI across India.

Qualitiviss has supported daily quality workflows at Wheels India for three years across more than 10 plants. QAI has recently been rolled out pan India to add recurring, evidence-backed analysis on top of the established operational system.

10+ plants across India
Three years in daily use
Recent pan-India QAI rollout
Quality workflows and recurring analysis
What this demonstrates

A practical progression from digitised quality operations to an AI Analyst operating on proven foundations.

03
DatVision AI · Production visual inspection

Ashok Leyland + Wheels India

Production vision operating across plants, lines and customer programmes.

DatVision AI has operated across four Ashok Leyland plants for three years and at Wheels India for one year. Deployments support end-of-line inspection and vision-based traceability, within more than 20 DatVision AI rollouts across multiple customers.

4 Ashok Leyland plants
Three years at Ashok Leyland
One year at Wheels India
20+ customer rollouts
What this demonstrates

Repeatable industrial vision deployment for inspection and traceability in live production environments.

04
DatVision AI · End-of-line wheel inspection

Wheels India

One inspection for every wheel variant.

A part-number recipe brings wheel model identification, measurements in millimetres and component counts into one end-of-line visual inspection. The inspection view highlights count exceptions for quality review.

Part-number and model recipe
Dimensions in millimetres
Expected versus detected counts
End-of-line quality review
What this demonstrates

Variant-specific visual inspection that shows the team which feature or count requires attention.

Read the full customer story

Manufacturing scale

From MSME and supplier operations to multi-plant enterprise programmes.

Existing systems retained

Dataviss adds an intelligence layer across the operational stack already in use.

Global deployment model

Designed for plant, site, regional and international operating footprints.

Explore the intelligence layer
Outcome Assessment

Bring one recurring decision. We’ll map how Dataviss would analyse it.

Show us the recurring work, operational problem or delayed decision. We will identify the minimum evidence required, the best-fit Analyst and the measurable outcome your first deployment should prove.

01

Define the recurring work

One review, investigation, evidence pack, case or decision that repeatedly consumes time.

02

Map the available evidence

The minimum ERP, QMS, SCADA, BMS, historian, vision or file-based sources needed.

03

Agree the success measure

Time released, cases processed, SLA performance, loss, working capital or risk—measured before expansion.

Start with one workload—not a platform-wide commitment
Expand only after your team validates the outcome
Outcome assessment

Choose a preferred discussion time. Bring one recurring decision or operational bottleneck; we will map the evidence, Analyst and first success measure.

Times are interpreted in your browser's local timezone and included with the request.