We have quite a few use cases that we have built. Not one, but many. I see a lot of value in the cognitive part of it: the IQ Bot. In the traditional RPA market, people have been doing it for a very long time now.
We have quite a few use cases that we have built. Not one, but many. I see a lot of value in the cognitive part of it: the IQ Bot. In the traditional RPA market, people have been doing it for a very long time now.
There's one use case that we did it for a U.S. organization for their accounts payable process. That's the biggest use case that we did. We took that and showcased it to all our customers, so they could get confidence. By doing that, we got three to four more leads out of it, increasing the business. That's a huge use case where we showcase the capabilities of IQ and its strongest aspects.
The cognitive is where everyone is heading to in the RPA platform. What really helps RPA to grow is the cognitive part of it. That's where the product is really good. Initially, it started out as RPA, but now there is a cognitive aspect to it. That's a key value to it.
An interesting thing: If you look at AA, the OCR capability is actually from a third-party. They don't have their own OCR in there. They use ABBYY or Tesseract. They should have their own engine built-in with their own IP. It increases the value rather than trying to use a third-party solution. That's where I see a lot of value.
As a product, it's been always very stable. The only thing that we wanted was it to be on the cloud. We saw at Imagine yesterday that now it's on cloud and will be more stable and accessible. People can start building bots in the click of a second. That's the good part. It's more stable now because it's on the cloud.
I don't think there were any challenges. Everybody who wants to do RPA can start very small. They do a PoC, build a few bots, and then they scale up. I don't see a challenge as long as you have the right people doing what they are trying to do. A lot of use cases in our organization are only two to three bots initially, and now, they have 40 to 50 bots. So, I don't think there is an issue in terms of scalability at all.
Technical support needs to be much faster. I also had the project delivery. I had six clients whom I looked after. Whenever we got stuck, it was all about sprinting. There was a two or three week sprint. Within that, if you just wait for two to three days, it doesn't make sense. The support needs to implode, because I was just talking to a customer now who came directly and asked us, "Can you give us a dedicated support team?" It's feedback from our customer that support takes too long.
It's just the time; the pure amount of time. Imagine processing 5,000 to 6,000 documents, how much time does that take if a person does it? It saves on the quality of work, because the quality can be bad when somebody's doing it. If a bot does the work, it's faster and comes with good quality. These are two important things along with the cost saving in the long run. That's where the value is.
I would rate it between a seven and eight (out of ten), which is good. I want it to improve on the support. They really need to improve on the support model. Also, the cognitive bit needs to be enhanced. I know that there are other products on the market who do much better than the product that we have. A lot of work can still go into it. One thing, it still cannot do is cursive writing. IQ Bots still cannot read cursive writing. That's where a lot of development effort can go into it and make it a great product.