4 posts categorized "Swiftype"

March 06, 2018

Lucidworks Announces Search as a Service

Not Your Grandfather's Site Search

Some of you may know that New Idea Engineering spun off a company called SearchButton.com in the mid-90s, offering Verity-powered site search for thousands of clients. Sadly, our investors insisted we violate the cardinal rule of business I learned at HP - "be profitable" - so when the "dot-com' bubble exploded, we were back to being New Idea Engineering again!

I remain a fan of hosted search to this day and have been pleasantly surprised to see companies like Algolia; Swiftype - now part of Elastic; and a few other "Search as a service" organizations reinventing the capabilities that we - along with a competitor Atomz> - offered more than 20 years ago! And I include with them the 'cloud-based' search services offed by other established enterprise search companies like Coveo, Microsoft, and until recently, Google.

That said, we've always strived to be fully vendor neutral when it comes to recommending products and services to our clients, and we go out of our way to understand and work with all of the major enterprise search vendors.

Over the last several months I've had the opportunity to use early releases of a product Lucidworks announced this morning: Lucidworks Site Search. As I said, I am a fan of hosted search - or 'search as a service'; and in full disclosure, I was a Lucidworks employee a few years back and yes, a shareholder.

I had an opportunity to talk with Will Hayes, Lucidworks' CEO, about Lucidworks' entry into the hosted search market. Even in its initial release, it looks pretty impressive.

First, Lucidworks Site Search is powered by the newest release of their enterprise product, Fusion 4.0, announced just last week and available for download. One of the exciting new capabilities in Fusion 4 is the full integration with Spark to enhance search with machine learning. It's not quite Google's "people like you" out of the box, but it's a giant step towards AI in the enterprise.

Fusion 4 also provides the ability to create, test, and move into production custom 'portable' search applications. When I first looked at the product last week, I confess to not having the vision to see just how powerful that capability is. It seems that the Fusion Site Search announced this morning is an example of a powerful, custom search app written specifically for site search.

But Lucid has great plans for their Site Search product. It can be run in the cloud, initially on AWS but soon expanding to other cloud services including Azure and Google. And reliability, you can elect to have Lucidworks Site Search span multiple data centers and even across multiple cloud services. As you'd expect in an enterprise product, it supports a wide variety of document formats, security, faceted navigation and a full management console. Finally, I understand that plans are in the works Lucidworks Site Search to be installed "on-prem" and even federate results (respecting document security) from the cloud and from your local instance at the same time.

Over the coming weeks and months I'll be writing more about Fusion 4, Lucid Site Search, and search apps. Stay tuned!

February 22, 2018

Search Is the User Experience, not the kernel

In the early days of what we now call 'enterprise search', there was no distinction between the search product and the underlying technology. Verity Topic ran on the Verity kernel and Fulcrum ran on the Fulcrum kernel, and that's the way it was - until recently.

In reality, writing the core of an enterprise search product is tough. It has to efficiently create an index of all the works in virtually any kind of file; it has to provide scalability to index millions of documents; and it has to respect document level security using a variety of protocols. And all of this has to deliver results in well under a second. And now, machine learning is becoming an expected capability as well. All for coding that no user will ever see.

Hosted search vendor Swiftype provides a rich search experience for administrators and for uses, but Elastic was the technology under the covers. And yesterday, Coveo announced that their popular enterprise search product will also be available with the Elastic engine rather than only with the existing Coveo proprietary kernel. This marks the start of a trend that I think may become ubiquitous.  

Lucidworks, for example, is synonymous with Solr; but conceptually there is no reason their Fusion product couldn't run on a different search kernel - even on Elastic. However, with their investment in Solr, that does seem unlikely, especially with their ability to federate results from Elastic and other kernels with their App Studio, part of the recent Twigkit acquisition.

Nonetheless, Enterprise search is not the kernel: it's the capabilities exposed for the operation, management, and search experience of the product.

Of course, there are differences between Elastic and Coveo, for example, as well as with other kernels. But in reality, as long as the administrative and user experiences get the work done, what technology is doing the work under the covers matters only in a few fringe cases. And ironically, Elastic, like many other platforms, has its own potentially serious fringe conditions. At the UI level, solving those cases on multiple kernels is probably a lot less intense than managing and maintaining a proprietary kernel.

And this may be an opportunity for Coveo: until now, it's been a Cloud and Windows-only platform. This may mark their entry into multiple-platform environments.

June 28, 2017

Poor data quality gives search a bad rap

If you’re involved in managing the enterprise search instance at your company, there’s a good chance that you’ve experienced at least some users complain about the poor results they see. 

The common lament search teams hear is “Why didn’t we use Google?” when in fact, sites that implemented the GSA but don’t utilize the Google logo and look, we’ve seen the same complaints.

We're often asked to come in and recommend a solution. Sometimes the problem is simply using the wrong search platform: not every platform handles every user case and requirement equally well. Occasionally, the problem is a poorly or misconfigured search, or simply an instance that hasn’t been managed properly. Even the renowned Google public search engine doesn’t happen by itself, but even that is a poor example: in recent years, the Google search has become less of a search platform and more of a big data analytics engine.

Over the years, we’ve been helping clients select, implement, and manage Intranet search. In my opinion, the problem with search is elsewhere: Poor data quality. 

Enterprise data isn’t created with search in mind. There is little incentive for content authors to attach quality metadata in the properties fields of Adobe PDF Maker, Microsoft Office, and other document publishing tools. To make matters worse, there may be several versions of a given document as it goes through creation, editing, reviews, and updates. And often the early drafts, as well as the final version, are in the same directory or file share. Very rarely does a public facing web site content have such issues.

Sometimes content management systems make it easy to implement what is really ‘search engine optimization’ or SEO; but it seems all too often that the optimization is left to the enterprise search platform to work out.

We have an updated two-part series on data quality and search, starting here. We hope you find it helpful; let us know if you have any questions!

June 22, 2017

First Impressions on the new Forrester Wave

The new Forrester Wave™: Cognitive Search And Knowledge Discovery Solutions is out, and once again I think Forrester, along with Gartner and others, miss the mark on the real enterprise search market. 

In the belief that sharing my quick first impression will at least start a conversation going until I can write up a more complete analysis, I am going to share these first thoughts.

First, I am not wild about the new buzzterms 'cognitive search' and "insight engines". Yes, enterprise search can be intelligent, but it's not cognitive. which Webster defines as "of, relating to, or involving conscious mental activities (such as thinking, understanding, learning, and remembering)". HAL 9000 was cognitive software; "Did you mean" and "You might also like" are not cognition.  And enterprise search has always provided insights into content, so why the new 'insight engines'? 

Moving on, I agree with Forrester that Attivio, Coveo and Sinequa are among the leaders. Honestly, I wish Coveo was fully multi-platform, but they do have an outstanding cloud offering that in my mind addresses much of the issue.

However, unlike Forrester, I believe Lucidworks Fusion belongs right up there with the leaders. Fusion starts with a strong open source Solr-based core; an integrated administrative UI; a great search UI builder (with the recent acquisition of Twigkit); and multiple-platform support. (Yep, I worked there a few years ago, but well before the current product was created).

I count IDOL in with the 'Old Guard' along with Endeca, Vivisimo (‘Watson’) and perhaps others - former leaders still available, but offered by non-search companies, or removed from traditional enterprise search (Watson). And it will be interesting to see if Idol and its new parent, Microfocus, survive the recent shotgun wedding. 

Tier 2, great search but not quite “full” enterprise search, includes Elastic (which I believe is in the enviable position as *the* platform for IoT), Mark Logic, and perhaps one or two more.

And there are several newer or perhaps less-well known search offerings like Algolia, Funnelback, Swiftype, Yippy and more. Don’t hold their size and/or youth against them; they’re quite good products.

No, I’d say the Forrester report is limited, and honestly a bit out of touch with the real enterprise search market. I know, I know; How do I really feel? Stay tuned, I've got more to say coming soon. What do you think? Leave a comment below!