The recognition rate prediction:
Proof of Concept (PoC).
With high document volumes, it is advisable to take a deeper look behind the scenes. The image quality, variety of invoices, reference data, centralised vs. decentralised structures, etc. result in an environment that fundamentally influences automation.
Step 1 – Basic analysis: Evaluate individual starting point
In the first step, the parameters mentioned are collected with ML and statistical methods based on sample data and compared with the empirical values of other companies.
The result is an expected rate for automated capturing.
Step 2 – Quality measurement
In a second step, we confirm and specify the expected automation rates with an objective measurement using a representative data set.
Step 3 – Potential assessment and final report
In a final step, the measurement and potential improvements through training data and model improvements are evaluated. Optionally, these improvements can be implemented immediately and the measurement carried out again.
Die Erkenntnisse fassen unsere Experten in einem Bericht zusammen.