Can a Well Worn Compass Help Enterprise Search Thrive?

September 4, 2019

In the early 1990s, Scotland Yard (which never existed although there is a New Scotland Yard) wanted a way to make sense of the data available to investigators in the law enforcement sector.

A start up in Cambridge, England, landed a contract. To cut a multi year story short, i2 Ltd. created Analyst’s Notebook. The product is now more than a quarter century old, and the Analyst’s Notebook is owned by IBM. In the span of five or six years, specialist vendors reacted to the Analyst’s Notebook functionalities. Even though the early versions were clunky, the software performed some functions that may be familiar to anyone who has tried to locate, analyze, and make sense of data within an organization. I am using “organization” in a broad sense, not just UK law enforcement, regulatory enforcement, and intelligence entities.

What were some of the key functions of Analyst’s Notebook, a product which most people in the search game know little about? Let me highly a handful, and then flash forward to what enterprise search vendors are trying to pull off in an environment which is very different from what the i2 experts tackled 25 years ago. Hint: Focus was the key to Analyst’s Notebook’s success and to the me-too products which are widely available to LE and intel professionals. Enterprise search lacks this singular advantage, and, as a result, is likely to flounder as it has for decades.

The Analyst’s Notebook delivered:

  • Machine assistance to investigators implemented in software which generally followed established UK police procedures. Forget the AI stuff. The investigator or a team of investigators focused on a case provided most of the brain power.
  • Software which could identify entities. An entity is a person, place, thing, phone number, credit card, event, or similar indexable item.
  • Once identified, the software — influenced by the Cambridge curriculum in physics — could display a relationship “map” or what today looks like a social graph.
  • Visual cues allowed investigators to see that a person who received lots of phone calls from another person were connected. To make the relationship explicit, a heavy dark line connected the two phone callers.
  • Ability to print out on a big sheet of paper these relationship maps and other items of interest either identified by an investigator or an item surfaced using maths which could identify entities within a cluster or an anomaly and its date and time.

Over the years, other functions were added. Today’s version offers a range of advanced functions that make it easy to share data, collaborate, acquire and add to the investigative teams’ content store (on premises, hybrid, or in the cloud), automate some functions using IBM technology (no, I won’t use the Watson word), and workflow. Imagery is supported. Drill down makes it easy to see “where the data came from.” An auditor can retrace an investigator’s action in order to verify a process. If you want more about i2, just run a Bing, Google, or Yandex query.

Why am I writing about decades old software?

The reason is that is read an item from my files as my team was updating my comments about Amazon’s policeware for the October TechnoSecurity & Digital Forensics Conference. The item I viewed is titled “Thomson Reuters Partners with Squirro to Combine Artificial Intelligence Technology and Data to Unlock Customer Intelligence.” I had written about Squirro in “Will Cognitive Search (Whatever That Is) Change Because of Squirro?

I took a look at the current Squirro Web site and learned that the company is the leader in “context intelligence.” That seemed similar to what i2 delivered in the 1990s version of Analyst’s Notebook. The software was designed to fit the context of a specific country’s principal police investigators. No marketing functions, no legal information, no engineering product data — just case related information like telephone records, credit card receipts, officer reports, arrest data, etc.

Squirro, founded in 2012 or 2013 (there are conflicting dates online) states that the software delivers

a personalized, real-time contextual stream from the sea of information directly to your workplace. It’s based on Squirro’s digital fingerprint technology connecting personal interests and workflows while learning and refining as user interactions increase.

I also noted this statement:

Squirro combines all the different tools you need to work with unstructured data and enables you to curate a self-learning 360° context radar natural to use in any enterprise system. ‘So What?’ Achieving this reduces searching time by 90%, significantly cutting costs and allows for better, more effective decision-making. The highly skilled Swiss team of search experts has been working together for over 10 years to create a precise context intelligence solution. Squirro: Your Data in Context.

Well, 2013 to the present is six years, seven if I accept the 2012 date.

The company states that it offers “A.I.-driven actionable Insights,” adding:

Squirro is a leading AI-platform – a self-learning system keeping you in the know and recommending what’s next.

I’m okay with marketing lingo. But to my way of thinking, Squirro is edging toward the i2 Analyst’s Notebook type of functionality. The difference is that Squirro wants to serve the enterprise. Yep, enterprise search with wrappers for smart software, reports, etc.

I don’t want to make a big deal of this similarity, but there is one important point to keep in mind. Delivering an enterprise solution to a commercial outfit means that different sectors of the business will have different needs. The different needs manifest themselves in workflows and data particular to their roles in the organization. Furthermore, most commercial employees are not trained like police and intelligence operatives; that is, employees looking for information have diverse backgrounds and different educational experiences. For better or worse, law enforcement intelligence professionals go to some type of training. In the US, the job is handled by numerous entities, but a touchstone is FLETC. Each country has its equivalent. Therefore, there is a shared base of information, a shared context if you will.

Modern companies are a bit like snowflakes. There’s a difference, however, the snowflakes may no longer work together in person. In fact, interactions are intermediated in numerous ways. This is not a negative, but it is somewhat different from how a team of investigators worked on a case in London in the 1990s.

What is the “search” inside the Squirro information retrieval system? The answer is open source search. The features are implemented via software add ons, wrappers, and micro services plus other 2019 methods.

This is neither good nor bad. Using open source reduces some costs. On the other hand, the resulting system will have a number of moving parts. As complexity grows with new features, some unexpected events will occur. These have to be chased down and fixed.

New features and functions can be snapped in. The trajectory of this modern approach is to create a system which offers many marketing hooks and opportunities to make a sale to an organization looking for a solution to the ever present “information problem.”

My hypothesis is that i2 Analyst’s Notebook succeeded an information access, analysis, and reporting system because it focused on solving a rather specific use case. A modern system such as a search and retrieval solution that tries to solve multiple problems is likely to hit a wall.

The digital wall is the same one that pushed Fast Search & Transfer and many other enterprise search systems to the sidelines or the scrap heap.

Net net: Focus, not jargon, may be valuable, not just for Squirro, but for other enterprise search vendors trying to attain sustainable revenues and a way to keep their sources of funding, their customers, their employees, and their stakeholders happy.

Stephen E Arnold, September 4, 2019

The New Lingo of Enterprise Search

August 28, 2019

Enterprise search is back. My Google Alert has been delivering market research reports which tell me that finding information is huge. Plus, there have been some announcements about funding which have surprised me. Examples include:

  • Capacity raised $13.2 million. Source: DarkCyber
  • LucidWorks snagged an additional $100 million. Source: Globe News Wire
  • Squirro pulled in additional funds, but the timing of the Salesforce investment and additional funding of this Zurich based company remains a bit of a mystery. Source: Venture Lab

These are just three examples plucked from my box of note cards about search vendors.

What’s interesting is the lingo, the jargon, and the argot these outfits are using. Frankly the plumbing is usually open source, a fact which the companies bury beneath the blizzard of buzzwords.

Here are some examples:

AI powered

actionable insights

artificial intelligence

cloud

cognitive

connect the dots

data mining

fusion

information mining

machine learning

natural language

pattern detection

platform

self learning

transform

The problem with the vendors collecting investment funds are easy to identify:

  1. The content processed is text. The unstructured information in videos, podcasts, messaging apps like WhatsApp, images like chemical structures and engineering drawings, etc. are not included.
  2. Indexing content residing on cloud platforms may work today, but as market dynamics shift, access to that content my be blocked or prohibited by regulations in certain countries
  3. Federation, on-the-fly so that real time information is available remains a challenge which typically requires script fiddling or new content filters
  4. Configuration of “smart” systems is not significantly different from the complex, time consuming, and expensive procedures which added friction to some Autonomy, Convera, Fast Search & Transfer, and similar systems’ deployment
  5. Maintenance is an issue, micro services work well in a low latency environment. Under loads, the magic of sub three second response can disappear
  6. Search remains an idiosyncratic solution. Many departments require specific features. As a result, enterprise search — regardless of the wrappers around open source information retrieval systems — is a series of customizations.

To sum up, enterprise search has failed to deliver for more than 50 years. Despite the optimism that investors have for “finding the next Google”, enterprise search vendors will find themselves hitting a revenue ceiling just as Autonomy, Fast Search, and similar firms did.

The fix was acquisitions and allegations of financial fancy dancing. If we assume that investors still dream of a 10x or higher return, is it possible that LucidWorks can generate sufficient revenue to pull off an IPO or a sale like Exalead, Vivisimo, and other search vendors were able to complete before the hammer fell?

This is an important question because new enterprise search vendors are popping up like mushrooms. The incumbents like Attivio, Coveo, Mindbreeze, and Sinequa are also trying to smash a ball over the fence.

Net net: Enterprise search appears to be putting on the worn slippers last used by the founders of Fast Search & Transfer. Maybe Microsoft will buy another enterprise search vendor? The problem is that enterprise search is easy to make visible with marketing LED lights. Delivering sustainable revenues is a far greater challenge when Amazon is a competitor and a platform enabler.

What happens when Amazon competes more aggressively, raises its prices, or bundles text search into another of its services?

Answer: Nothing particularly beneficial for the investors in new and improved enterprise search solutions based on Lucene/Solr and dusted with disco glitter.

Stephen E Arnold, August 28, 2019

Enterprise Search: AI and a Low Spend

August 26, 2019

DarkCyber Read “Capacity Raises $13.2 Million to Index Emails, Files, and More with AI.” The company was founded in 2017. We noted this passage:

Capacity (formerly Jane.ai), [is] a startup developing a platform that indexes data from apps, teams, and more and enables users to search through the corpus using natural language.

Plus, the system learns and improves over time.

The company’s funding to deliver AI, multi-source enterprise search is “over $21 million.”

One of the founders is CEO David Karandish, formerly the CEO of Answers.com. He is quoted as saying:

[Capacity] is an intuitive, intelligent AI-powered Teammate who gives employees instant access to the information they need to do their jobs well.

The indexing system can process content from such systems as:

  • ADP human resource information
  • Box
  • NetSuite
  • Google Gmail
  • Microsoft Exchange
  • Microsoft OneDrive
  • Sage human resource information
  • Salesforce
  • ServiceNow
  • Zendesk

The system includes “a chatbot with natural language processing capabilities that integrates with popular messaging apps such as Slack and Skype.”

We noted this statement:

Capacity can deliver company-wide announcements, like daily news and event notifications, and onboard new hires by providing access to forms that need to be completed. For customers with websites that have FAQ sections, it can be made public-facing to help cut down on customer service requests.

If Capacity can deliver, outfits like LucidWorks will have some explaining to do to its investors.

Stephen E Arnold, August 26, 2019

Enterprise Search and Grease Management

June 7, 2019

I see some crazy stuff. Every once in a while, a really crazy item crosses my desk. The example I wish to highlight today is called “Enterprise Search Software Market to depict huge growth, Key Methodologies, Top Players: SharePoint, IBM, Lucidworks, Microsoft FAST, Oracle, Amazon CloudSearch, Apache Lucene, Attivio.” My hunch is that rolling in Amazon and Microsoft cloud revenues will make almost any market look like Popeye the Sailor Man. The reality is that enterprise search came and went in a blaze of litigation and embarrassment. Some of the exhaust seems to be emanating from the Hewlett Packard litigation related to the former medical device maker’s acquisition of an enterprise search vendor.

Enterprise search has overpromised and under delivered for about 50 years. Elsewhere I have recounted the adventures of services which most people don’t recall or simply knew nothing about. Remember InQuire, the service with forward truncation? A more recent fumble is the disappearance of those cheerful yellow Google Search Appliances, its staff, and the marketing collateral promising an end to the misery of traditional enterprise search solutions.

The buzz has not died down at at Reports Monitor. You can read their remarkable news release at this link. Forget the incredible hyperbole of “huge growth.” Hello, Reports Monitor, one can download a perfectly good enterprise search system from open source repositories. There are low cost systems available from outfits like Funnelback. You can get a next generation system from vendors of intelware. Don’t recognize the term? Don’t worry. These vendors don’t know what enterprise search means. And there are some companies which this report does not list as players. Want these names? Sorry, that’s information for which I charge a fee. Believe me. Reports Monitor and perhaps you, gentle reader, don’t know about these companies either.

What causes me to write about a report which is a bit on the wild side? How about this passage:

Key Insights:

  • Complete in-depth analysis of the Grease Management in Commercial Kitchens
  • Important changes in market dynamics.
  • Segmentation analysis of the market.
  • Emerging segments and regional markets.
  • Historical, on-going, and projected market analysis based on volume and esteem.
  • Assessment of niche industry players.
  • Market share analysis.
  • Key strategies of major players.

Yep, grease management. Now we’re getting to the heart of slippery data and even more slippery reports about enterprise search. The report provides region-wise data. Great stuff.

News flash: Enterprise search left the dock and took on water. Some outfits torpedoed their investors, customers, and partners. Others have tried to become business intelligence, analytics, even customer service support systems. Did not work too well.

Why?

Enterprise search is not a general purpose application. Significant work is necessary to make it possible for employees to find information in what are silos or in oddball lingo. Furthermore important people like lawyers, product researchers, and big wheels like to keep their information secret. An enterprise search system has failure baked in unless it is tailored to a quite specific problem. But at that point why not buy an eDiscovery system, a lab notebook system, or a niche solution for the eager beavers in marketing?

Maybe I am too harsh on the grease management angle. That may be closer to the truth than Reports Monitor realizes.

Stephen E Arnold, June 7, 2019

Amazon Moved a Knight. Google Pushes a Pawn

April 10, 2019

If you care about search and retrieval, you may be interested in the chess game underway between Amazon and Google. Amazon seized the initiative by embracing the open source Elasticsearch. Google, an outfit whose failures in search are known to anyone who licensed a Google Search Appliance, has responded. The pawn Google nudged forward is Elastic, the outfit which has been a big dog in search and retrieval for several years.

According to “Elastic and Google Cloud Expand Elasticsearch Service Partnership”:

Elastic (NYSE: ESTC) and Google Cloud (GCP) announced the expansion of their managed Elasticsearch Service partnership to make it faster and easier for users to deploy Elasticsearch within their Google Cloud Platform (GCP) accounts. Building upon the partnership to deliver Elastic’s Elasticsearch Service on GCP, the companies announced a fully managed, cloud-native integration for discovery, billing, and support for Elasticsearch Service within the GCP Console.

We also circled this statement, which is quite fascinating when interpreted in the context of Amazon’s open source tactic:

Elastic’s Elasticsearch Service on GCP gives users a turnkey experience to deploy powerful Elastic Stack features of Elasticsearch and Kibana, including proprietary free and paid features such as security, alerting, machine learning, Kibana spaces, Canvas, Elasticsearch SQL, and cross-cluster search. In addition, users can deploy new curated solutions for logging, infrastructure monitoring, mapping and geospatial analysis, and APM; optimize compute, memory, and storage workloads using Elastic’s customizable deployment templates such as hot-warm architecture for the logging use case; and upgrade to the latest version of Elasticsearch and Kibana as soon as it is released with a single click.

The chess timer is Amazon’s. Will the company make a lucid move?

Stephen E Arnold, April 10, 2019

The Search Wars: When Open Starts to Close

March 12, 2019

Compass Search. The precursor. The result? Elasticsearch. No proprietary code. Free and open source. The world of enterprise search shifted.

As a result of Shay Bannon’s efforts, an alternative to proprietary search and interesting financial maneuvers, an individual or organization could download code and set up a functional enterprise search system.

There are proprietary search systems available like Coveo. But most of the offerings are sort of open sourcey. It is a marketing ploy. The forward leaning companies do not use the word search to market their products because zippier functionality is what brings tire kickers and some buyers.

The landscape of search seems to be doing its Hawaii volcano act. No real eruption buts shakes, hot gas, and cracks have begun to appear. The lava flows will come soon enough.

a bezos art

The path is clear to the intrepid developer.

The tip off is Amazon’s announcement that it now offers an open distro for Elasticsearch. Why is Amazon taking this step? The company explains:

Elasticsearch has become an essential technology for log analytics and search, fueled by the freedom open source provides to developers and organizations. Our goal is to ensure that open source innovation continues to thrive by providing a fully featured, 100% open source, community-driven distribution that makes it easy for everyone to use, collaborate, and contribute.

DarkCyber’s briefings about Amazon’s policeware initiative suggest that the online bookstore is adding another component to its robust intelligence system and services.

The move involves or will involve:

  • Entrepreneurs who will see Amazon as creating low friction for new products and services
  • Partners because implementing search can be a consulting gold mine
  • Users
  • Developers who will use an Amazon “off the shelf” solutions
  • Competitors who may find the “other open source” Elasticsearch lagging behind the Amazon “house brand”.

The move is not much of a surprise. Amazon seeks to implement its version of IBM’s 1960s style vendor lock in. Open source is open source, isn’t it? A version of the popular Elasticsearch system which has utility in commercial products to add ons which help make log files more mine-able. Plus search snaps into the DNA of the Amazon jungle of services, functions, features, and services. Where there is confusion, there are opportunities to make money.

Adding a house brand to its ecosystem is a basic tactic in the Amazon playbook. Those T shirts with the great price are Amazon’s, not the expensive stuff with a fancy brand name. T shirts and search? Who cares?

What’s the play mean for over extended proprietary search systems which may never generate a pay day for investors? A lot of explaining seems likely.

What the play mean for Elastic, the company which now operates the son of Compass Search? Some long off site meetings may be ahead and maybe some chats with legal eagles.

What’s the play mean for vendors using Amazon as back end plumbing for their enterprise or policeware services? A swap out of the Elasticsearch system for the Amazon version could be in the cards. Amazon Elasticsearch will probably deliver fewer headaches and lost weekends than using the Banon-Elastic version. Who wants headaches in an already complex, expensive implementation?

The Register quotes an evangelist from AWS as saying:

“We will continue to send our contributions and patches upstream to advance these projects.”

DarkCyber interprets this action and Amazon’s explanations from the perspective and context of a high school football coach:

“Front line, listen up, fork that QB. I want that guy put down. Hard. Let’s go.”

Amazon. The best defense is a good offense, right?

The coach shouts:

“Let’s hit those Sheep hard. Arrrgh.”

Stephen E Arnold, March 12, 2019

Beyond Search for 2019

January 1, 2019

I started Beyond Search to focus on new developments in enterprise search. That was in 2008. After 10 years of focusing on search, I have decided to retain the url but shift Beyond Search to cover the hidden Internet and lesser known Internet services. The blog will undergo a modest redesign and be called “DarkCyber Annex.”

Why an annex?

The modified Beyond Search blog will include information which supplements my weekly DarkCyber video. DarkCyber has been in production for one year, and it is—as far as I know—the only weekly video news program reporting about intelware, hidden Internet sites, and cyber crime.

To keep the videos in the 10 minute range, my team and I have to prune stories and content.

DarkCyber Annex, therefore, will be the online location for some of our additional content. We will continue to include links in the weekly videos, but now a version of the video story will appear in the DarkCyber Annex and include hyperlinks to source documents.

The flow of stories to Beyond Search will go down, and those assisting me in creating content for DarkCyber Annex will increase the flow of stories on the themes I have identified.

I plan to leave the Beyond Search content online. The 16,899 stories will be searchable but frozen. Looking back, enterprise search companies often described a fantastical world in which instant access was both marketed and sold.

That contributed to the implosion of the enterprise search sector. Today, if one wants search, many choose Lucene / Solr. Vendors of old school proprietary information retrieval systems will still market aggressively, pay consulting firms to sing the praises of the systems, and hold conferences which recycle words and concepts which are decades old.

Enough. Stale conferences. Endless repetition of hard-to-believe claims. Weird Eisenhower / BCG charts comprised of subjective silliness. Flaccid essays in online blogs and news services about “content management.” Yada yada yada.

For me, the subject is not just uninteresting. Enterprise search is a case study in what is likely to happen to other technologies in search of a solution informed by watching Star Trek. Explaining enterprise search in terms of “governance” in our Facebook world is shallow.

In 2019, I will try to make clear that intelware, not search, is where information access is today. Banging in key words still works, but the innovators are pushing into function spaces that deliver on some of the wild and crazy claims made in the salad days of Autonomy, Convera, Endeca, Fast Search & Transfer, and the dozens upon dozens of other companies I tracked in my career.

Enterprise search has fallen on its sword. New solutions have become available, but so far enterprises remain unaware of some of the most promising vendors.

DarkCyber videos and DarkCyber Annex will try to fill the information void. After all, we know traditional search is not too useful, right?

Stephen E Arnold, January 1, 2018

Elastic Bounces and Rolls Away from Other Search Vendors

October 6, 2018

Please, do not confuse what Bing and Google deliver as “search” with the type of information access system which is available from Elastic. The founder of Compass Search (remember that?) has emerged as the big dog in the information access world. At a time when direct competitors like Attivio, Coveo, and Funnelback are working overtime to become something other than information access providers, Elastic and its Elasticsearch ecosystem have pulled off a digital kudzu play.

The evidence is not the raucous Elastic developer conferences. The proof is not the fact that most policeware vendors use Elastic as the plumbing for their systems. The hard facts are dollars.

I learned that Elastic pulled off its IPO and closed up 94.4 percent. Talk about happy investors. Those believers in the Shay Bannon approach must be turning cartwheels. For more financial insights, navigate to “Search Company Elastic Nearly Doubles on First Trading Day.” The write up states:

The debut rally is all the more pronounced because it comes on a down day for the broader market, particularly the tech sector.

Elastic, it seems, represents a bright spot.

Congrats to Mr. Bannon and the Elastic team.

There are some outfits likely to take a hard look at their “search” business. Among them will be the vendors of proprietary search systems like the companies I mentioned above. Most of these outfits continue to find a way to make their investors happy. Attivio bounces between business intelligence and search. Coveo roves from search to customer support. Funnelback, well, Funnelback chugs along because one of their management team told me that the company is not open source. I wonder if that wizard wishes it were playing open source canasta.

The more interesting company to consider in the context of the Elastic solid triple in the search big leagues is LucidWorks. This company played its open source card. The company flipped CEOs, changed its focus, and emulated the polymorphic approach to search that the proprietary vendors followed. LucidWorks then found itself facing the Amazon search system staffed helpfully with a LucidWorks’ veteran or two. LucidWorks has consumed more than $100 million in investment capital, pushed founder Marc Krellenstein down the memory hole, and watched as the Elastic outfit blasted past LucidWorks and into the lushness of the IPO. Both companies had similar business models. Both companies leveraged the open source development community. Both companies followed similar marketing scripts.

But there was a difference.

Shay Bannon provided vision and he figured out that he needed a strong supporting cast. The result is that Elastic moved forward, added capabilities, made prudent decisions about supplemental modules, and offered reasonable for fee option to those who tried out the open source version of the search system and then moved to pay for service and other goodies available from Elastic.

The result?

The future for LucidWorks now looks a bit different. The company has to find a way to pay back its investors. The firm’s Elastic like business model may have to be reevaluated. Heck, the product line up may be require a refurbishing comparable to those performed on automobile programs which take an interesting vehicle and turn it into a winner.

Unfortunately fixing up search vendors is not as easy to do in real life. A TV show has the benefit of post production and maybe some color and sound experts to spiff up the automobile.

Image result for bitchin rides

Competitors like LucidWorks will have to spiff up their 1956 automobiles in order to catch customers’ eyes as Elastic rolls rapidly into the future.

Search doesn’t work that way.

The question becomes, “What will LucidWorks do?”

Even those of us in Harrod’s Creek know what Elastic will do. The company will chug along and become the go to way to provide utility search, log analysis, and other basic functions to outfits which appear to be independent high tech search wizards.

Stephen E Arnold, October 6, 2018

Wake Up Time: IBM Watson and Real Journalists

August 11, 2018

I read “IBM Has a Watson Dilemma.” I am not sure the word “dilemma” embraces the mindless hyperbole about Vivisimo, home brew code, and open source search technology. The WSJ ran the Watson ads which presented this Lego collection of code parts one with a happy face. You can check out the Watson Dilemma in your dead tree edition of the WSJ on page B1 or pay for online access to the story at www.wsj.com.

The needle point of the story is that IBM Watson’s push to cure cancer ran into the mushy wall composed of cancerous cells. In short, the system did not deliver. In fact, the system created some exciting moments for those trying to handcraft rules to make Dr. Watson work like the TV show and its post production procedures. Why not put patients in jeopardy? That sounds like a great idea. Put experts in a room, write rules, gather training data, and keep it update. No problem, or so the received wisdom chants.

The WSJ reports in a “real” news way:

…Watson’s recommendations can be wrong.

Yep, hitting 85 percent accuracy may be wide of the mark for some cognitive applications.

From a practical standpoint, numerical recipes can perform some tasks to spin money. Google ads work this magic without too much human fiddling. (No, I won’t say how much is “too much.”)

But IBM believed librarians, uninformed consultants who get their expertise via a Gerson Lehrman phone session, and from search engine optimization wizards. IBM management did not look at what search centric systems can deliver in terms of revenue.

Over the last 10 years, I have pointed out case examples of spectacular search flops. Yet somehow IBM was going to be different.

Sorry, search is more difficult to convert to sustainable revenues than many people believe. I wonder if those firms which have pumped significant dollars into the next best things in information access look at the Watson case and ask themselves, “Do you think we will get our money back?”

My hunch is that the answer is, “No.”

For me, I will stick to humanoid doctors. Asking Watson for advice is not something I want to do.

But if you have cancer, why not give IBM Watson a whirl. Let me know how that works out.

Stephen E Arnold, August 11, 2018

Thoughtspot: Confused in Kentucky over AI for BI Plus Search Plus Analytics

August 3, 2018

i read “Nutanix Co-Founder Lures Away Its President to Be New CEO at ThoughtSpot.” The headline is a speed bump. But what puzzled me was this passage:

ThoughtSpot Inc. has hired Nutanix Inc.’s president as its new CEO. Sudheesh Nair joins ThoughtSpot about three months after the Palo Alto enterprise search business raised $145 million in a funding round that valued the company at more than $1 billion.

I added the emphasis on the phrase “enterprise search business.”

Search is not exactly the hottest buzzword around these days. After shock from the FAST Search & Transfer and IBM Watson adventures I hypothesize.

Now here’s the pothole: The ThoughtSpot Web site states:

Search & AI Driven analytics.

I noted the phrase “next generation analytics for the enterprise.” Plus, ThoughtSpot is a platform.

But what about artificial intelligence? Well, that’s part of the offering as well.

Remarkable: A Swiss Army knife. Many functions which may work in a pinch and certainly better than no knife at all.

But what’s the company do? Gartner suggests the firm has vision.

That helps. The first time around with FAST ESP and IBM Watson-like marketing the slow curves went right by the batters and the buyers. The billion dollar valuation is juicy as well. Another Autonomy? Worth watching.

Stephen E Arnold, August 3, 2018

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