AI Document Extraction


vWork is a job scheduling and dispatch software. vWork aims to reduce the cost of managing field jobs for mid-sized businesses with complex or high-volume workflows. The software is used by many organisations, including Toll Group, Foodstuffs and Rockgas.

project SUMMARY

UVLens is the number 1 rated sun safety app on Android and iOS. UVLens shows the danger level of ultraviolet (UV) rays throughout the day and provides personalised recommendations based on the user’s skin type.

- 500k+ worldwide users
- Featured by Apple App Store
- Editors Choice on Google Play Store‍

vWork customers process large quantities of work orders requesting or reporting on jobs which must be added to the platform. These are mainly in the form of PDF email attachments and vary significantly from client to client, and sometimes from job to job. These work orders were manually entered into the system - a time-consuming process.

vWork was interested in exploring potential solutions to automating this manual task to increase their ability to scale and add more value to the platform for the customers. Spark 64 was engaged to conduct exploratory research and report delivery to assess how this could be achieved.

The Solution

We presented a report identifying and comparing potential solutions, ranging from completely custom options to fully managed 3rd party platform. These solutions had different tradeoffs for vWork’s use case, mainly coming down to quality and ease of implementation for the managed solutions, and improved customisation and price for the more custom solutions. Solutions explored ranged from SaaS to fully managed turn-key solutions from Xtracta, Docparser, AWS and Azure.

The Outcome

A wide range of potential solutions for document extraction were investigated to find those which showed the most promise for vWork’s specific use case and  considerations. The tradeoffs, pricing models, recommendations, and implementation plan were presented, which allowed vWork to proceed with the next steps in creating a proof of concept integrated with their backend.

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