The last years have seen tremendous improvements with regards to the quality of pattern recognition in unstructured data. The reason for this is next to hardware improvements mainly a group of algorithms, which go by the name of neural nets or deep learning. A key feature of these approaches is that given enough training data, they form their own set of rules in order to achieve a certain goal. This way millions of implicit rules may be defined to successfully recognize even rather complex patterns.
Criteria to discover attractive process automation projects, where visual information play a crucial role:
- Currently the process is cost-intensive and/or a faster decision creates substantial value
- A (trained) human could make a good decision mainly based on text
- There is enough data available (as a rule of thumb: 500 - 10.000 documents. This, of course, is highly dependent on the use-case)
In our experience, only by combining knowhow of internal operations with natural language processing expertise, projects can be framed well. Feel free to approach us with questions, especially whether we deem your project to be technically feasible.