Name: Knotest
Availability: InStock

Put your pilot to the test

88%of AI pilots never reach production

Teams adopting AITeams building AI

The goal

Vision

InspecSpider · Hong Kong Productivity Council

Edison Awards 2024 Silver Winner

The challenge
InspecSpider inspects structures at height. Tests with simulated fog exposed weaknesses in the vision model's segmentation, despite otherwise stable performance.
The tests
The team used test logs to pinpoint failures, then added difficult examples to the training data.
The results
23.7%
Robustness improvement
After these changes, robustness improved by 23.7% in the tested scenario.

Demand forecasting and replenishment

The challenge
A growing bar wanted to replace manual forecasts with AI. It used Knotest to check whether the system could improve stock planning with its own sales data.
The tests
Tests covered promotions, holiday demand, and weather changes. Before the pilot began, the team agreed on metrics, success criteria, and conditions for rollout.
The results
53.7%
stockout rate improvement
An eight-week A/B study tested six top-selling Category A beers, rotating every two weeks. It recorded a 53.7% improvement in stockout rate, alongside improvements in overstock, holding costs, and planning time.

Supplier document processing

The challenge
An Asian food-and-beverage group spent too much time processing supplier documents by hand. It used Knotest to assess an AI provider before committing to the system.
The tests
The team tested poor scans, overlapping stamps, and inconsistent formats. It agreed on performance targets and rollout criteria with the provider.
The results
65.3%
processing time reduction
A one-month A/B study compared manual and AI processing of invoices, delivery orders, and credit notes. Processing time fell by 65.3%, with improvements in accuracy and error rate.