When we started we weren’t really aware of how this concept would evolve into an Industrial solution. We had direction upto one point, but the scope was very obscure. And if you have experience with SDLC, you’ll know that this is a risky challenge.
With Computer Vision, we were aware about how CNN generally works but there was much research to be done. We quickly learnt how CV works, but still only minimal info was available to connect CV concepts to the actual utilization needed by the client. We developed an OCR and what it did was basically extract info from a Cause and Effect table. Now you might ask that OCR is easily available in markets then why did we create one from scratch? Our client had limitations bringing in a market OCR and hence they were using their own OCR to predict characters and extract info.
The difference we brought was in terms of quality. We upgraded the OCR to a huge extent, and this was our first milestone - Developing our own Industrial OCR and using it to extract info from Cause-Effect-Action tables. So we would exactly replicate and assemble together components and their relationships in terms of Cause-Effect-Action.