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Blog> Use Cases

Coseer Gets It Right

Coseer Gets It Right

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We’ve talked at length about point-and-shoot AI for enterprise search. With Coseer, just point at the data you’re interested in, and shoot.

But instant results are worthless if they aren’t accurate.

Coseer Gets It Right

Enter the virtuous cycle of AI. Accurate systems attract traffic. They provide an incentive for the user not to try alternative methods to get their job done. So, a virtuous cycle picks up – accurate systems reward the user, driving more traffic to the AI system, which trains it better, in turn making the system more accurate.

With the above in mind, it’s easy to understand why Coseer’s point and shoot capability and high accuracy go hand in hand. Because the system is so user-friendly and results are almost instantaneous (no data tagging, and deployment takes just 4-12 weeks as opposed to months), users return again and again – allowing for more iterations and better training faster.

Some AI paradigms, like deep learning, while amazing for structured data, take much more time and effort to setup. Because expensive SMEs must go through vast stores of data manually tagging relevant information, training takes a long time and can be very costly. In the long run, there is less time for multiple iterations and results often disappoint. The IBM Watson/MD Anderson  debacle is a famous case where data prep and protracted setup time led to diastrous results.

We’ve also tested Coseer against other Natural Language Processing AI approaches such as Stanford NLP and Ling-Pipe , two of the leading software packages in this area. Both claim 98% accuracy, but if you ask them to process real-world data, the probabilistic nature of language means they only agree 70% of the time. We know because we tested this in 2015, asking both Stanford and Ling-Pipe to extract the noun phrases from a corpus consisting of one week’s content posted by a popular Wall Street Twitter account.

Relative Accuracy of Stanford NLP vs. Ling-pipe

Leading NLP solutions agree with each other only 70% of the time for something as basic as Noun Phrase Extraction. What our Wall Street experiment demonstrates is we can only be 70% confident that any noun phrases extracted by industry-standard NLP tools are accurate.

Setup a call to learn more about how Coseer can deliver 95-98% accurate results for your enterprise search tool in just 4-12 weeks.

 

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