This past week OpenText announced a partnership with Google Cloud (GCP), that announcement lifted OpenText’s share price to his highest ever level. At first blush, the excitement seemed odd, as frankly, everyone has a partnership with Google, Amazon, and Microsoft. Working to unpack the real relevance of this deal for both OpenText & Google reveals an intriguing partnership strategy.
This week my colleague, Alan Pelz-Sharpe, and I spent time with Alfresco at its annual analyst event. The product updates and customer examples were interesting, and the talk turned downright compelling when CTO, founder and visionary, John Newton, took the stage to describe how AI will remake content and process automation, freeing workers who are …
Once a year Information Management professionals travel from around the world to attend the AIIM Conference. It is the premier event for networking, education and industry gossip. As such it is particularly important for Deep Analysis, as we get to talk with dozens of end user organizations and find out what they are thinking, planning and doing in the world of Information Management. It’s a chance for us to truly check the industry pulse, make new contacts and reconnect with technology buyers from far and wide.
I find the world of OpenText observers fall into two well defined camps. The first camp believes that OpenText’s business is in serious decline and dependent almost entirely on maintenance fees from legacy products. The other camp sees OpenText as steady, slow, profitable but dangerously reliant on maintenance fees from legacy products. Though there are threads of accuracy in both camps, the reality is somewhat different. As of 2019 OpenText is a major player undertaking a key, and to date, pretty successful, pragmatic pivot.
To be fair, Artificial Intelligence and Machine Learning have been used for a long time in enterprise applications but their usage has really been for really complicated scenarios such as enterprise search (e.g., for for proximity, sounds etc) or sentiment analysis of social media content. But it has never been easy to use machine learning for relatively simpler use cases. Additionally, no vendor provided any SDKs or APIs using which you could use machine learning on your own for your specific use cases.