Lead processing · Production

Qlik AutoML and Analytics Platform Drives Efficiency for Integra, Samsung, Zift Solutions, and Other High-Tech Customers

The problem

High-tech companies faced slow manual processes for evaluating loan prospects, lengthy data acquisition times from CRMs, and fragmented data sources, making fast informed decisions difficult.

Workflow diagram · grounded in source
1
Loan prospect evaluation request
trigger
“With 30 seconds to manually vet viable leads for purchase, making informed decisions was a challenge”
2
AutoML filters and predicts outcomes
ai_action
“With Qlik AutoML, Integra's loan prospects are filtered and probable outcomes revealed in real time”
3
Queries automated at scale
output
“35K queries were automated the first week — saving $35K”
Reported outcome

Integra automated 35K queries in the first week saving $35K with annual savings projected to reach $1M; Samsung increased field visit efficiency by 20%; Zift Solutions reduced integration build time by 80% and cut data acquisition from up to 24 hours to 30 seconds; and Microland reduced resolution times.

Reported metrics
Queries automated in first week35K
Cost savings in first week$35K
Projected annual savings$1M
Field visit efficiency20%
Show all 7 reported metrics
queries automated in first week35K
cost savings in first week$35K
projected annual savings$1M
field visit efficiency20%
time to build integrations80%
time to data acquisitionfrom up to 24 hours to 30 seconds
resolution timesreduced resolution times
Reported stack
QlikQlik AutoMLQlik Application Automation
Source
https://www.qlik.com/us/solutions/industries/high-tech-business-intelligence
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Integra automated 35K queries in the first week saving $35K with annual savings projected to reach $1M; Samsung increased field visit efficiency by 20%; Zift Solutions reduced integration build time by 80% and cut dat…

What tools did this team use?

Qlik, Qlik AutoML, Qlik Application Automation.

What results were reported?

Queries automated in first week: 35K; Cost savings in first week: $35K; Projected annual savings: $1M; Field visit efficiency: 20% (source-reported, not independently verified).

How is this lead processing AI workflow structured?

Loan prospect evaluation request → AutoML filters and predicts outcomes → Queries automated at scale.