If you Google “OEM: build versus buy,” you’ll get nearly a million results. It almost doesn’t matter what area of technology you pick, at some point there’s going to be a build versus buy bridge to cross.
For example, let’s take embedded analytics. That’s a hot topic right now among bloggers and industry analysts. ISVs that build line-of-business applications see embedded analytics as a way to differentiate their products. And, since they’re software companies, they could develop and embed the analytics themselves, right? Yes, they could.
One of the smartest ways to grow your business is to acquire companies with complementary (and sometimes competing) products and services. You get a ready-made customer base and established products that fit nicely into your long-term business strategy.
Attivio joined forces with our partner Persistent Systems to build an app that provides a 360° view of the customer on the Salesforce Service Cloud. Engage 360 unifies information from across distributed data sources, such as similar cases, prior solutions, and internal knowledge bases.
Attivio 5.5—the latest release of our market leading Cognitive Search and Insight Platform—has a lot going for it. If you just want a quick summary of all its new features, the launch press release is a good place to start.
But I’m going to focus on one—the platform’s use of machine learning to improve relevancy. After all, relevancy is the heart of cognitive search.
In a recent blog, we talked about Attivio’s “Sherlock” cognitive search campaign, which takes aim at IBM’s Watson. We noted that organizations deploy cognitive search platforms to boost employee productivity, foster innovation, and gain greater insight from their data. But to achieve those goals, they often take on huge professional services from “mega vendors” like IBM that don’t deliver an effective cognitive solution.
Benedict Cumberbatch, star of the BBC series “Sherlock,” has a problem. Sherlock’s stream-of-consciousness deductive speeches must be delivered at warp speed— “100 miles an hour”—and that’s hard to pull off without mistakes.
But, of course, all that speed makes sense. Holmes observed, processed, and bang! Insight. That’s rapid time to value.
