AWS Kendra: A Somewhat Elastic Approach to Enterprise Search

May 12, 2020

Elastic, Shay Banon’s Version 2 of Compass, has a hurdle to jump over. Elasticsearch has been a success. The Lucene-centric “system” which some call ELK has become a go-to solution for many developers. Like Lucidworks (It does?) and many other “enterprise search and more” vendors, Elasticsearch delivers information retrieval without the handcuffs of options like good old STAIRS III or Autonomy’s neuro-linguistic black box.

Amazon took notice and has effectively rolled out its own version of enterprise search based on … wait for it … the open source version of Elastic’s Elasticsearch. The service has been around since Amazon hired some of the Lucidworks (It does?) engineers more than five years ago after frustration with the revolving doors at that firm became too much even by Silicon Valley standards. Talk about tension. Yebo!

Amazon has reinvented Elasticsearch. The same process the Bezos bulldozer has used for other open source software has been in process for more than 60 months. Like the system’s Playboy bunny namesake, Kendra has a few beauty lines in her AWS exterior.

A tweak here (access to Amazon’s smart software) and a tweak there (Amazon AWS pricing methods), and the “new” product is ready for prime time, ready for a beauty contest against other contestants in the most beautiful IR system in the digital world.

Amazon Launches Cognitive Search Service Kendra in General Availability” reports:

Once configured through the AWS Console, Kendra leverages connectors to unify and index previously disparate sources of information (from file systems, websites, SharePoint, OneDrive, Salesforce, ServiceNow, Amazon Simple Storage Service, relational databases, and elsewhere).

Does this sound like federated search or the Palantir Gotham approach to content?

Well, yes.

The reason is that most enterprise search vendors like Coveo, Attivio, X1, IBM Omnifind (also built on Lucene), and dozens of other systems make the same claims.

The reality is that these systems do not have the bits and pieces available within a giant cloud platform with quite a few graduates of an Amazon AWS training program ready to plug in the AWS solution. For example, if a government agency wants the search in Palantir, no problem. Palantir deploys on AWS. But if that government agency wants to use Amazon’s policeware services and include search, there’s Kendra.

You can get a free copy of the DarkCyber Amazon policeware report’s executive summary by requesting the document at this link.

What does Amazon bring to the enterprise search party?

The company has more than 200 services, features, component, and modules on the shelf. Because enterprise search is not a “one size fits all”, the basic utility function has to fit into specific enterprise roles. For most enterprise search vendors, this need for user function customization is a deal breaker. Legal doesn’t want the same search that those clear minded home economics grads require in the marketing department. Microsoft SharePoint offers its version of “enterprise search” but paints over the cost of the Microsoft Certified professionals who have to make the search system work Fast. (Yep, that’s sort of an inside search joke.)

Amazon AWS provides the engine and the Fancy Dan components can be plugged in using the methods taught in the AWS “learn how to have a job for real” at a company your mom uses to shop during the pandemic. Amazon and Microsoft are on a collision course for the enterprise, and the Kendra thing is an important component.

The official roll out is capturing headlines, but the inclusion of Lucene-based search invites several observations:

  • Despite AWS’ pricing, an Amazon enterprise search system allows the modern information technology professional to get a good enough service with arguably fewer headaches than other options except maybe the SearchBlox solution
  • Enterprise search becomes what it has been for most organizations: A utility. Basic information retrieval is now an AWS component and that component can be enhanced with SageMaker, analytics, and other AWS services.
  • Amazon wins even if Kendra does not win the hearts and minds of IBM Omnifind, Inbenta, and Algolia users. Why? Most of the cloud based enterprise search vendors support the AWS platform. What are the choices? The wonky HP cloud? The “maybe we will kill it” Google Cloud? Azure, from the outfit that cannot update Windows 10 without killing user computers who activate game mode? Plus, dumping Kendra for another TV star inspired search system is easy. Chances are that, like Palantir, AWS hosts and supports that competitive system too.

Net net: The fight with Microsoft is escalating. The Bezos bulldozer will run over open source outfits and probably some AWS customers. But Kendra’s turning her gaze on the bountiful revenues of Microsoft in the enterprise. Will Amazon buy a vendor of Word, PowerPoint, and Excel clones?

Exciting times, maybe not just because of enterprise search? Why did those defectors from Lucidworks (It does?) embrace Lucene and not SOLR? Maybe they did that too?

Stephen E Arnold, May 12, 2020

The Crazy Search Market Report: May 4, 2020 Edition

May 4, 2020

DarkCyber is pondering a new feature called “Crazy Search Report.” The “search” refers to enterprise search. The “crazy” refers to the assertions and marketing hoo-hah in news releases about the steady stream of in depth analysis of the market for enterprise search.

Yeah, I know that sounds crazy. Well, that’s why the crazy search report will be useful. We will identify the producer of the report and include some content from the news releases issued to cheerlead for these five figure “believe it or not” compilations.

Let’s look at the first report in the series.

This is called “Global Coronavirus Impact and Implications on Enterprise Search Market Research Report 2019 Analysis and Forecast To 2029.” The publicity was generated by something called factmr.com on May 1, 2020.

Here’s the hook paragraph, that’s the one that will make you buy the report from Research Moz. Is this outfit in the same league as Bain, Booz, Allen, and McKinsey? You decide:

Companies in the Enterprise Search market are vying suggestive steps to tackle the challenges resulting from the COVID-19 (Coronavirus) pandemic. Exhaustive research about COVID-19 is providing present-day techniques and alternative methods to mitigate the impact on Coronavirus on the revenue of the Enterprise Search market.

The news release also talks about the enterprise search landscape. I remember writing a book, published by Pandia Press, called “The Landscape of Enterprise Search.” Happy coincidence maybe?

Are these some factoids to make you want to buy this report? Sure, for example:

…The report ponders over the various factors that are likely to impact the overall dynamics of the Enterprise Search market over the forecast period (20XX-20XX) including the current trends, business expansion opportunities and restraining factors amongst others. As per the market report suggested by ResearchMoz.us, the global Enterprise Search market is expected to register a CAGR growth of ~XX% during the forecast period and attain a value of ~US$XX by the end of 20XX.

Okay, the numbers are left out. You have to pay before you get the alleged factoids. That definitely makes me lust after a copy not.

What’s interesting is the list of companies allegedly profiled and X-rayed in the document. Note: I alphabetized the company names, but the Moz outfit does not bother with this convention. My comments are in parentheses.

Attivio Inc (business intelligence maybe?)

Concept Searching Limited (Microsoft add in from far, far way from the US)

Coveo Corp (customer support and assorted buzzwords)

Dassault Systemes (product engineering search)

Expert System Inc (semantic utility, focus on mobile)

Google (not in the search business)

Hyland (ISYS Search which dates from the 1980s)

IBM Corp (Lucene plus Vivisimo plus home grown code and Watson. I can’t forget Watson.)

Lucid Work (Typo. The company’s name is Lucidworks.)

Micro Focus (Autonomy)

Oracle (Secure Enterprise Search, RightNow, Endeca, and others)

Marklogic Inc (XML database company with proprietary extensions)

Microsoft (Fast Search & Transfer plus assorted acquisitions and home grown tomfoolery)

SAP AG (Who knew?)

X1 Technologies (desktop search and eDiscovery originally from Idealab year ago)

How much is the report? The news release does not say, but we held our breath and clicked the Research Moz link and learned that the document costs $3,900.

That’s it. Crazy stuff for a crazy market sector.

Stephen E Arnold, May 4, 2020

Enterprise Search Craziness: Destiny Adjacency

May 1, 2020

The enterprise search vendors are not to blame. The finger of ineptitude writes boldly:

Enterprise Search Market each qualitative and quantitative records analysis to provide an overview of the destiny adjacency around Enterprise Search Market for the forecast duration, 2020-2025.

You can read the original at this link. Enterprise search has tried a number of snappy phrases to make a utility the potent heart of a 21st century enterprise; for example:

  • Semantic meaning
  • Natural language processing
  • Artificial intelligence
  • Precision, recall, and relevance. Yikes, delete those loser words.

DarkCyber believes that “destiny adjacency” is the all-time leader in the meaningless baloney fest that is pulled into the orbit of enterprise search.

Yep, “destiny adjacency”. Maybe a T shirt? A tattoo?

Stephen E Arnold, May 1, 2020

Remote Work and Enterprise Search: Implement Now!

April 28, 2020

The US and other countries has been shut down for more than a month. Companies of all sizes are struggling for revenue. The shift to WFH (work from home) is not exactly going on as smoothly as paint at a pre lockdown Peugeot plant.

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The enterprise search idea articulated by a person once affiliated with IBM Watson is a stunner. You can get the full scoop in the online publication RTInsights. (No, this RT is not part of the Russian propaganda system.)

Making Remote Work More Effective with Enterprise Search” argues that the WFH crowd can be productivity pythons. Forget the kids, the loneliness, the hassles with shopping, the security goblins, and the fear of losing one’s job. Put them out of your mind, WFH’ers. You can be a productivity python.

Sort of.

First, your employer — assuming you have one — must have an enterprise search in place. Failing that, your employer must spend money to license a suitable service. Hey, why not Sinequa, the French system which also does Big Data, analytics, and phenomenal marketing.

Now there are a couple of very minor issues to address; for example:

  • Conducting a content inventory, determining what information can be accessed by an authorized WFH’er.
  • The security and access controls must be defined, put in place, tested, and deployed.
  • The indexing cycles must be determined because WFH’er presumably put in their 12 hour days across time zones, from a variety of computing devices, and in chunks. (Someone has to remove the Amazon packages from the door step before a bad actor removes the inviting parcels with a smile logo.)
  • A workflow for getting employee generated content into the system and then getting the “real time indexing” which vendors stress their system performs to index in a reliable manner.
  • Assisting employees who use the WFH system and cannot find the document a colleague said was in the system on the Zoom call that ended five minutes ago. The basic questions are, “Where is the document? When will it be available? Who’s in charge of this clown car?

Second, candidate information must be located, vetted, and converted to a format that the enterprise search system can process. Videos, audio files, images, and proprietary file formats may be a bit of a challenge in terms of time and resources.

Third, the system must be made to work. No, I mean it, deliver results employees or authorized users need. How many enterprise search systems deliver on this final point?

The write up explains:

Almost all knowledge-intensive organizations have a digital workplace that includes enterprise search, which connects employees to the content they need to complete a given task. Companies typically either deploy a rudimentary open-source kit that relies on search queries using keywords or a larger ecosystem like Microsoft, Google, or IBM, which tend to exclude content and data stored outside of the ecosystem.

What?

Oh, here’s the point:

Now is the time for organizations to think about the way employees access content platforms and how that is impacting employee productivity, knowledge sharing, and competitive advantage.

Based on the research Martin White and I did for oru book Successful Enterprise Search Management, the time required to deploy an enterprise search system was measured in months, often years. Tossing in the WFH requirement is going to add more time and cost to those sensitive to data access, indexing cycles, optimization, and other easy-to-ignore factors.

The benefits of providing enterprise search for WFH’ers remind me of the IBM Watson promises about smart software: Failure and massive costs, a loss of stakeholder value, and the distinction to be removed from Houston’s cancer hub.

To sum up, Sinequa’s sales pitch wrinkled the DarkCyber forehead a tiny bit:

  • Glittering generalities about off site access to certain content is not something one just “thinks about.” Real management effort is required to avoid loss of trade secrets, sensitive information, and data which may be subject to government restrictions.
  • The data supporting the assumption “better, faster, cheaper search yields more productivity (whatever that is). There is zero evidence that WFH’ers will be more or less productive if enterprise search is available. Right now, finding information is more like a Zoom call, not a session online hunting through results lists and waiting for results lists to appear.
  • Phishing and other exploits. Security is not automatic. Security takes work. Oracle tried to sell its search system with Oracle security. No one in my experience was prepared to go through the hoops necessary to implement secure search. The result silos. What’s the cost for the WFH cohort? Probably more than some organizations are able to pay. (The May 12, DarkCyber video news program profiles a free-for-now open source solution to certain types of exploits. That’s a solution for those with handy infosec skills.)

Most applications used by WFH’ers include some type of search function. When information is not available, send an email or, better yet, hop on a Zoom call. And don’t forget Google, the millennials’ Swiss Army knife for information, or some social media scanning.

Enterprise search has not created productivity pythons in the more than 50 years information retrieval systems have been available.

Net net: Using Covid, WFH, and rusted buzzwords like enterprise search may not move the revenue meter. Invoking the tired, cheers-for-hire outfits like Gartner and IDC won’t do the job either. New types of information access systems are available. For examples, check out CyberOSINT: Next Generation Information Access. Even millennials will find some of these newer systems a refreshing findability option. As for enterprise search, its day in the sun faded with vendors’ inability to deliver results for licensees. Don’t believe me? Just ask former customers of Delphis, Entopia, Fast Search & Transfer, and the other precursors of today’s laborers in the search-and-retrieval Incan potato terraces.

Stephen E Arnold, April 28, 2020

Austrian Enterprise Search Gets Upgrade

April 23, 2020

When it comes to search innovation, people think about Silicon Valley or Japan. Austria, however, has its own high tech search solution from Iphos IT Solutions. Open PR shares news about Iphos IT Solutions’ newest search endeavor in the article, “SearchIT 2020-Even More Features & Functions For The Enterprise Search Solution searchIT.”

SearchIT 2020’s upgrade comes at an important time, because more employees are working from home during the COVID-19 pandemic. They need quick access to their company’s network from self isolation. The enhanced features and new function for SearchIT 2020 will make telecommunication seamless and guarantee employees are as productive, if not more, during quarantine.

Based on specially designed AI, SearchIT 2020 offers:

“SearchIT indexes and processes internal company data from a wide variety of sources, such as databases, file servers, mail servers, or various cloud storage sources. Finding data across all these sources is made easy with the full-text search function. The high degree of automation as well as many additional features not only provide users with an efficient and secure search tool, but also with the possibility of easy-to-handle document management, knowledge management, or the creation of comprehensive data archives.”

Since searchIT 2020 is built on AI, it does more than basic enterprise search applications. It allows users to build automatic data archives, starting data with third parties, and media monitoring. New features that are included in the upgrade include integrations of new search sources, dynamic report creation, meta and special searches with extended query syntax, preview function, explorer view, and automated language recognition.

Iphos IT Solutions provided solutions for large corporations to small and medium sized businesses. The pricing varies for all projects, but it is made to be affordable for any business while providing large scale services.

Whitney Grace, April 23, 2020

Enterprise Search: Not Exactly Crazy but Close

April 13, 2020

I think I started writing the first of three editions of the Enterprise Search Report in 2003. I had been through the Great Search Procurement competition for the US government’s search system. The original name for the service was FirstGov.gov (the idea was that the service was the “first” place to look for public facing government information. The second name was USA.gov, and it was different from FirstGov because the search results were pulled from an ad supported Web index.

The highlight of the competition was Google’s losing the contract to Fast Search & Transfer. (Note: The first index exposed to the public was the work of Inktomi, a company mostly lost in the purple mists of Yahoo and time.) Google was miffed because Fast Search & Transfer had teamed with AT&T and replied to the SOW with some of the old fervor that characterized the company before Judge Green changed the game. I recall one sticking point: Truncation. In fact, one of the Google founders argued with me about truncation at a search conference. I pointed out that Google had to do truncation whether the founders wanted to or not. My hunch is that you don’t know much about truncation and what it contributes. I won’t get into the weeds, but the function is important. Think stemming, inflections, etc.

I examined more than 60 “enterprise” search systems, including the chemical structure search systems, the not-so-useful search tools in engineering design systems like AutoCAD, and a number of search systems now long forgotten like Delphis and Entopia, among others.

I have also written “The New Landscape of Search” published by Pandia and “Successful Enterprise Search Management” with Martin White, who is still chugging along with his brand of search expertise. Of course, I follow search and retrieval even though I have narrowed my focus to what I call intelware and policeware. These are next-generation systems which address the numerous short coming of the oversold, over-hyped, and misunderstood software allowing a commercial enterprise to locate specific items of interest from their hotchpotch of content.

In this blog, Beyond Search/DarkCyber I write about some enterprise search systems. In general, I remain very critical of the technologies and the mostly unfounded assertions about what a search-and-retrieval system can deliver to an organization.

With this background, I reacted to “Enterprise Search Software Comparison” with sadness. I was not annoyed by the tone or desire to compare some solutions to enterprise content finding. My response was based on my realization about how far behind understanding of enterprise search’s upsides and downsides, the gap between next-generation information retrieval systems and the “brand” names, and the somewhat shallow understanding of the challenges enterprise search poses for licensees, vendors, and users.

The write up “compares” these systems as listed in the order each is discussed in the source article cited above:

  • IBM Watson Discovery
  • Salesforce Einstein Search
  • Microsoft Search
  • Google Cloud Search
  • Amazon Kendra
  • Lucidworks
  • AlphaSense.

Each of these system merits a couple of paragraphs. For comparison, the discussion of systems in the Enterprise Search report typically required 15 or more pages. In CyberOSINT, I needed four pages for each system described. I had to cut the detail to meet the page limit for the book. A paragraph may be perfect for the thumb typing crowd, but detail does matter. The reason is that a misstep in selecting enterprise software can cost time and money and jobs. The people usually fired are those serving on the enterprise search system procurement team. Why? CFOs get very angry when triage to make a system work costs more than the original budget for the system. Users get angry when the system is slow (try 120 seconds to find a document in a content management system and then learn the document has not been indexed), stakeholders (the investment in search cannot be recovered without tricks, often illegal), and similar serious issues.

Let’s look at each of these systems described in the write up. I am going to move forward in alphabetical order. The listing in the source implies best to worst, and I want to avoid that. Also, at the end of this post, I will identify a few other systems which anyone seeking an enterprise search system may want to learn about. I post free profiles at www.xenky.com/vendor-profiles. The newer profiles cost money, and you can contact me at benkent2020 at yahoo dot com. No, I won’t give you a free copy. The free stuff is on my Xenky.com Web site.

AlphaSense. This is a venture backed company focused on making search the sharp end of a business intelligence initiative. The company is influenced by Eric Schmidt, the controversial Xoogler. The firm has raised about $100 million. The idea is to process disparate information and allow users to identify gems of information. AlphaSense competes with next-generation information services like DataWalk, Voyager Labs, and dozens of other forward looking firms. Will AlphaSense handle video, audio, time series data, and information stored on a remote workers’ laptop? Yeah. To sum up: Not an enterprise search solution; it is a variant of intelware. That’s no problem. AlphaSense is a me too of a different category of software.

Amazon Kendra. Amazon has a number of search solutions. This is Lucene. Yes, Lucene can deliver enterprise search; however, the system requires a commitment. Amazon’s approach is to put enterprise search into AWS. There’s nothing quite like the security of AWS in the hands of individuals who have not been “trained” in the ways of Amazon and Lucene.

Google Cloud Search. This is the spirit of the ill fated Google Search Appliance. The problems of GSA are ameliorated by putting content into the Google Cloud. What’s Google’s principal business? Yep, advertising. Those Googlers are trustworthy: Infidelity among senior managers raises this question, “Can we trust you to keep your body parts out of our private data?” You have to answer that question for yourself. (Sorry. Can’t say. Legal eagles monitor me still.)

IBM Watson Discovery. Okay, this is Lucene, home brew, and acquired technology like Vivisimo. Does it work? Why not ask Watson. IBM does have robust next-generation search, but that technology like IBM CyberTap is not available to the author of the article or to most commercial organizations. So IBM has training wheels search which requires oodles of IBM billable hours. Plus the company has next-generation information access. Which is it? Why not ask Watson? (If you used ITRC in the 1980s, you experienced my contribution to Big Blue. Plus I took money. None of that J5 stuff either.)

Salesforce Einstein Search. If a company puts its sales letter and contacts into this system, one can find the prospect and the email a salesperson sent that individual. Why do company’s want Salesforce search? When a salesperson quits, the company wants to make sure it has the leads, the sales story, etc. There are alternatives to Salesforce’s search system. Why? Maybe there are sufficient numbers of Salesforce customers who want to control what’s indexed and what employees can see? Just a thought.

Microsoft Search. I would like to write about Microsoft Search. (Yep, did a small thing for this outfit.)  I would like to identify the acquisitions Microsoft completed to “improve” search. I would like to point out that Microsoft is changing Windows 10 search again. But that’s the story. One flavor of Microsoft Search is Fast Search & Transfer. It is so wonderful that a competitive solution is available from outfits like Surfray, EPI Server, and even Coveo (yep, the customer support and kitchen sink vendor). Why? Microsoft Search is very similar to the Google search: Young people fooling around in order to justify their salaries and sense of self worth. The result? I particularly like the racist chat bot and the fact that Microsoft bought Fast Search & Transfer as the criminal case for financial fraud was winding through Norway’s court system. Yep, criminal behavior. Why? Check out my previous write ups about Fast Search & Transfer.

Lucidworks. Okay, I did some small work for this outfit when it was called Lucid Imagination. Then the revolving door started to spin. The Lucene/Solr system collected many, many millions and started its journey to … wait for it… digital commerce and just about anything that could be slapped on open source software. Can one “do” enterprise search with Solr? Sure. Just make sure you have money and time. Lucidworks’ future is not exactly one that will thrill its funding sources. But there is hope for an acquisition or maybe an IPO. Is Lucidworks a way to get “faceted search” like Endeca offered in 1998? Sure, but why not license Endeca from Oracle? Endeca has some issues, of course, but I wanted to put a time mark in this essay so the “age” of Lucidworks’ newest ideas are anchored with a me-too peg.

What vendors are not mentioned who can implement enterprise search?

I will highlight three briefly, just to make clear the distortion of the enterprise market that this article presents to a thumb typing millennial procurement professional:

  1. Exalead spawned a number of interesting content companies. One of them is Algolia. It works and has some Exalead DNA.
  2. SearchIT is an outfit in Europe. It delivers what I consider a basic enterprise search system.
  3. Maxxcat produces a search appliance which is arguably a bit more modern than the Thunderstone appliance.
  4. Elastic Elasticsearch. This is the better Compass. How many outfits use Elasticsearch? Lots. There’s a free version and for-fee help when fans of Shay Bannon get stuck. Check out this how to.

There are others, of course, but my point is that mixing apples and oranges gives one a peculiar view of what is in the enterprise search orchard. It is better to categorize, compare and contrast systems that perform “enterprise search” functions. What are these? It took me 400 pages to explain what users expect, what systems can deliver, and the cost/engineering assumptions required to deliver a solution that is actually useful.

Search is hard. The next-generation systems point the way forward. Enterprise search has, in my opinion, not advanced very far beyond the original Smart system or IBM STAIRS III.

PS. Notice I did not use the jargon natural language processing, semantics, text analytics, and similar hoo haa. Why? Search has a different meaning for each worker in quite distinct business units. Do you expect a chemical engineer looking for Hexamethylene triperoxide diamine to use a word or a chemical structure? What about a marketing person seeking a video of a sales VP’s presentation at a client meeting yesterday? What about that intern’s Instagram post of a not-yet-released product prototype? What about the information on that sales VP’s laptop as he returns to his home office after a news story appeared about his or her talk? What about those human resource personnel data files? What about the eDiscovery material occupying the company’s legal team? What about the tweet a contractor sent to a big client about the cost of a fix to a factory robot that trashed a day’s production? What about the emails between an executive and a sex worker related to heroin? (A real need at a certain vendor of enterprise search!) Yeah! Enterprise search.

Stephen E Arnold, April 13, 2014

Ancient Search Recipes: Bread Pork Chops

December 16, 2019

I noted a report in the Times of Israel titled “Cache of Crypto-Jewish Recipes Dating to Inquisition Found in Miami Kitchen.” One of the recipes explained how to make a pork chop from bread and milk. (Dairy? Guess so.) Here’s what you and I can whip up using this ancient recipe:

image

The cookbook contains information which the author “didn’t think to question the idiosyncratic customs her mother and grandmothers practiced in the kitchen.”

By coincidence, my news alert spit out this article in the same list: “The Growth of Cognitive Search in the Enterprise, and Why It Matters.”

Magic. Bread pork chops created from zeros and ones.

Search matters. Cognitive search matters more. Who buys? The enterprise.

The write up recycles the equivalent of the break pork chop formula. Mix jargon, sprinkle with the notion of federated data, and bake until the checks clear the bank.

The article is fascinating, and it overlooks a few milestones in the history of enterprise search. What for example? Glad you asked:

  1. Forrester, the Wave folks, has created a report for its paying customers which reveal that search is now cognitive, able to tap dark data, and ready for prime time. Again! The Wave returns.
  2. Big companies are into search, including Microsoft  with its Fast inspired solution and Amazon Kendra with an open source how de doo to Elastic and LucidWorks. Some use old spices; others, open source flavoring with proprietary special seasonings.
  3. Outfits which have been around for more than a decade like Coveo are now smarter than ever in their decade long effort to pay off their patient investors
  4. Autonomy gets a nod despite the interesting trial underway in the UK.

The point is that enterprise search is going to be in the news whether anyone wants to revisit hyperbole which makes the chatter around artificial intelligence and quantum computing seem rational and credible.

Here’s a quick refresher about why untapped data in an organization is likely to remained untapped or at the very least not tapped by vendors of smart key word search systems:

First, data are in silos for a reason. No enterprise search system with which I am familiar can navigate the permissions and access controls required to put siloed data in one index. There’s a chance that the Amazon blockchain permissions system can deliver this, but for now, the patents are explanations and federated enterprise search is a sales pitch.

Read more

Amazon Enterprise Search: Kendra

December 6, 2019

Years ago I worked on a small project for a company connected to the film industry. At one of those Hollywood “lunches”, a person pointed across the restaurant and said, “That’s Kendra.” I had zero idea who or what a Kendra was. It turned out that “Kendra” was famous, a star. She was a Playboy bunny! She looked like most of the other female appearing types in the room.

Amazon’s Kendra is not a Playboy bunny. Kendra is Amazon’s new online enterprise search service. It looks pretty much like all the other online enterprise search services in the room.

There’s a difference. This enterprise search service is mounted on the Amazon platform, and it has open source goodness, some proprietary fashion flair, and hooks into numerous good looking advanced AWS services.

Amazon says in “Amazon Kendra”:

Amazon Kendra is a highly accurate and easy to use enterprise search service that’s powered by machine learning. Kendra delivers powerful natural language search capabilities to your websites and applications so your end users can more easily find the information they need within the vast amount of content spread across your company.

I am not sure what “accurate” means, but it sure differentiates the service from the odd ball results some enterprise search solutions deliver. The “easy” part is also relative and subjective. Which of AWS’s more than 170 functions and services does Kendra get along with? Too soon to tell.

Some observations:

  • The enterprise search vendors who have convinced venture capitalists to invest hundreds of millions in enterprise search and retrieval may be curious about Amazon’s sudden aggressiveness
  • The enterprise search companies themselves now have to decide: Put services on AWS or go elsewhere despite the costs and resources required
  • The AWS customers may want to kick the tires of the AWS service and postpone a procurement of a venture funded old school search engine. (Talking about NLP and machine learning is one thing. Delivering productized services from an AWS dashboard is another.)

Net net: For organizations struggling to federate and provide blockchain centric information access management, Amazon’s Kendra might look quite fetching.

Stephen E Arnold, December 6, 2019

ElasticSearch: A Push for Log File Revenue?

November 13, 2019

Elasticsearch had a moment in the sun. For several years it was the go to way to deploy a low cost, reasonably usable search and retrieval system. Then came the venture funding to a clump of outfits talking about search in terms of jargon that would have made a 1950s’ Madison Avenue executive reach for the bottle in his desk drawer.

To get a sense of the pressure exerted on ElasticSearch, navigate to “How to Get Started with Kibana.” Why battle with the tens of millions in fresh cash stuffing the pockets of Algolia, Coveo, and LucidWorks, among other 21st century enterprise search vendors with a penchant for buzzwords?

Do the pivot and keep one’s hand on the Elasticsearch throttle.

The write up explains:

Kibana is a powerful tool for visualizing data in Elasticsearch.

The article provides a sunny overview of how

you can explore practically any type of data, from text documents to machine logs, application metrics, ecommerce traffic, sensor telemetry, or your company’s business KPIs.

A KPI is, if you did not know, is a key performance indicator. What’s performance? What’s key? Heck, what’s an indicator? There you go. Modern methods for Kibana.

Net net: Elasticsearch is making it clear that it too is moving beyond search.

Search, however, has been moving beyond itself for decades. But my tagline for anything to do with the interesting and slightly sordid past of enterprise search is, “Who cares?”

Elasticsearch stakeholders.

Stephen E Arnold, November 13, 2019

Coveo: A 15 Year old $1 Billion Start Up Unicorn in Canada!

November 6, 2019

I read “Coveo Raises US$172M at $1B+ Valuation for AI-Based Enterprise Search and Personalization.” The write up states:

Search and personalization services continue to be a major area of investment among enterprises, both to make their products and services more discoverable (and used) by customers, and to help their own workers get their jobs done, with the market estimated to be worth some $100 billion annually. Today, one of the big startups building services in this area raised a large round of growth funding to continue tapping that opportunity.

Like Elastic, Algolia, and LucidWorks, Coveo is going to have to generate sufficient revenues to pay back its investors. Perhaps the early supporters have cashed out, but the new money is betting on the future.

Coveo was founded in Quebec City more than a decade ago. The desktop search company Copernic spun off Coveo in 2004. The original president was Laurent Simoneau. Mr. Tetu is an investor with great confidence in enterprise software, and he has become the “founder”, according to the write up. In April 2018, Coveo obtain about $100 million from Evergreen Coast Capital.

DarkCyber recalls that Coveo has moved from Microsoft-centric search to search as a service to customer experience and now personalization.

In 2005, I wrote this about the upsides of the Coveo approach in the Enterprise Search Report I compiled for an outfit lost to memory:

Coveo is a reasonably-priced, stable product. Any organization with Microsoft search will improve access to information with a system like Coveo’s. Microsoft SharePoint customers will want to do head-to-head comparisons with other “solutions” to Microsoft’s native search solution. Coveo has a number of features that make it a worth contender. Other benefits of the Coveo approach include:

  • Web-based administration tool allows straightforward configuration and monitoring of the system.
  • Automatic indexing of new and updated documents in near real-time.
  • Includes linguistic and statistical technologies that can identify the key concepts and the key sentences of indexed documents. Provides automated document summaries for faster reading and filtering.
  • Groups information sources into collections for field-specific searches.
  • The product is attractively priced.
  • Tightly integrated with other Microsoft products and Windows-based security regimes.
  • Customer base has grown comparatively quite rapidly and customers tend to speak well of the product.

I noted these considerations:

The software is Windows-centric – both in terms of its own software as well as document security settings it tracks – which may be an issue with certain types of organizations. You will have to assign permissions to index to allow the ASP.NET worker process user to access the index. The task is simplified, but it can be overlooked. Administrative controls are presented without calling attention to actions that require particular attention. Coveo is still however able to search content on any operating system, application, or server. Other drawbacks of the Coveo search system include:

  • There is limited software development support to allow customization or extensions of the core technology to other applications, although the company is expanding the product’s reach through Dot Net-based APIs.
  • When the system is installed and its defaults accepted, the “Everyone” group is enabled. Administrators will want to customize this setting. A wizard would be a useful option for organizations new to enterprise search.
  • No native taxonomy support, except through partner Entrieva.
  • Achieving scalability beyond hundreds of millions of documents requires appropriate resources.

My final take on the company was:

Coveo Enterprise Search meets many distinct needs of the small and medium-sized business that has standardized on the Microsoft platform, while still providing a few critical advanced search capabilities. Perhaps more importantly, CES minimizes search training, system maintenance, and other cost “magnets” that typically accompany an enterprise search deployment.
Like a handful of other products in this report, you can test Coveo out first, via a free download of a document-limited version.

The challenge for Copernic is to make enough sales and to generate robust sustainable income. This is the uphill run that Algolia, Elastic, LucidWorks, and probably a number of other enterprise search vendors face. Perhaps an outfit like Xerox will buy up, which would be one way to get the investors their money?

DarkCyber wishes Coveo the best. But a start up unicorn? No, that is not exactly correct for a 15 year old outfit. This push to make the investors smile is not for the faint hearted or those who have a solid grasp of the formidable enterprise search options available today. Plus there are outfits like Diffeo and other next generation information access systems available for free (Eleasticsearch) or bundled with other sophisticated information management tools (Amazon, search, managed blockchain, workflows, and a clever approach to vendor lock in.)

One tip: Don’t visit Quebec City in February during a snow storm.

Stephen E Arnold, November 6, 2019

Stephen E Arnold, November 5, 2019

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