Success stories

Process automation: OpenText Captiva for a public sector agency

Hand pointing at laptop screen

Our customer is a large sized European governmental agency, with over 52,000 employees distributed across a central administration and over 20 regional subsidiaries.

€600k

savings in 2 year

20x

Productivity increase

+200k

documents digitized

solution

Solution

Our 10+ year track record in working with input management solutions, our agile project approach and our government consulting expertise made AmeXio the right partner for this.

After a thorough assessment of the customer needs, the choice of OpenText Intelligent Capture to simplify and speed up documents’ digitization and exportation was obvious. Being OpenText certified experts allowed us to implement Capture, but also to go a step further. Besides streamlining the existing processes, we trained and shared all best practices tips with
end users, so they could make the most out of the software.

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As OpenText experts, we had no doubts when it came to picking Capture. But more than installing this software, it’s important to train employees so they feel 100% confident in using the system and don’t get lost in the adaptation

Result

The use of machine learning technology was key to optimize information flows. Automatic metadata extraction and classification further automate document processing. With this new approach, our client was now able to process 100 documents in less than 10 minutes, an exponential increase from the previous 3 to 5 documents processed in the same time frame. The automation of this task also significantly reduced mistakes made during the manual process, creating an easier, more user-friendly way of working.

With the new system, it’s estimated that this governmental agency will saved 71k euros and digitize more than 65.000 documents in one year. The
estimations for next year look even more promising, as our client expects to have saved 520k euros and successfully digitized over 150.000 documents until the end of the year.

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