Crossing the Abbyy Road | Analyst Notes | Deep Analysis

Crossing the Abbyy Road

Apologies for the title of this note, but I couldn’t resist it – and in my defense, its a pretty good summary of the note to come.

Abbyy is a firm that I have known on and off for many years, as an OCR/Capture company. Indeed I have recommended them to clients that have sophisticated, multilingual capture needs to meet. But its also a firm that I have never spent too much time looking at as core capture technology is not my thing. I leave that sort of thing to my good friends Harvey Spencer at HSA.

But a couple of weeks ago, I had a chance to meet with Abbyy in Nashville, TN, as their annual conference overlapped with ARMA’s at the same venue. Though I left with no doubt that capture is still left right and center for Abbyy, I was also intrigued by their moves into process management and intelligent automation. In particular, I was particularly struck by two of their products, Process IQ & Content IQ. We will try to write up in more detail in the future on these products. The reason for my interest is that technology areas such as capture, process, and content management have all tried to plow (plough) their own furrows, and historically have been dismissive of the true value of others. Though there is a long way to go, that is slowly starting to change.

In fact, just this past week I was in a briefing with my colleague Connie Moore (the process queen) and discussed the future roadmap of a digital process automation vendor. Core to that future corporate vision is the inclusion of advanced capture. Just as conversely. core to the future corporate vision of Abbyy is process management. It’s a recurring theme, RPA vendors want to automate more sophisticated processes, BPM vendors wish to capture more regular transactions. Content management firms want to gain more insight into the content they store; analytics vendors want to manage their content more carefully. The lines are starting to blur, and frankly, it’s about time. But turning such huge and well-established technology silos is no easy undertaking, so patience is unfortunately still required.

That being said, what is common in all of these focus shifts is the use of Machine Learning and Artificial Intelligence. These technologies are seen as the glue to hold the disparate elements together. It’s good to see, and its much needed by buyers and end-users of technology. The challenge moving forward, though, is two-fold. The first challenge is to maintain this broad and holistic view of customer needs. Simple in theory but surprisingly hard for any vendor to sustain. The second is to understand the limitations of AI and work within them. AI & Machine Learning are powerful tools, but without good quality data and clear business ownership, they can be at best blunt objects, at worst, destructive. Even so, such bridges to adjacent technology areas, though logical, have been rare in the past. Yet, these are encouraging signs for Abbyy et al. and the road ahead.

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