IBM: There Are Doubters
December 31, 2015
Watson has its works cut out for itself in 2016. I read “IBM Set to Drop 13% in 2015.” When one is tossing around a $100 billion outfit, the thought of a share drop is disconcerting. Will Alibaba or Jeff Bezos step in. Fixing up the Washington Post may be trivial compared with an IBM scale challenge.
According to the write up:
Much of the disappointment in the tech company is because it has been unable to replace its hardware and software legacy products with new cloud-based and AI products — at least not at a rate that would pull IBM’s revenue up. Its major branded product in new age technology is Watson. While Watson has been the source of press releases and small customer alliances, outsiders have trouble seeing what it does to sharply increase IBM’s sales. Granted, Watson may be one of the most impressive product advances among large companies in the sector recently, but what it does for IBM may be very modest.
Somewhat of a downer I perceive.
The smart software thing is not new. In the last 18 months, awareness of the use of various numerical recipes has increased. Faster chips, memories, and interconnections have worked their magic.
The challenge for IBM is to make money, not just marketing hyperbole. The crunch is that expectations for certain technologies are often more robust than possible in a market.
Watson is, when one keeps its eye on the ball, is a search and content processing system. The wrappers make it possible to call assorted functions. Unlike Palantir, which has its own revenue fish to catch, IBM is a publicly traded company. Palantir does its magic as a privately held company, ingesting money at rates which would make beluga whale’s diet look modest.
But IBM has exposed itself. The Watson marketing push is dragged into the reality of IBM’s overall company performance. In 2016, IBM Watson will have to deliver the bacon, or some of the millennialesque PR and marketing folks will have an opportunity to work elsewhere. Talk about smart software is not generating sustainable revenue from smart software.
Stephen E Arnold, December 31, 2015
Index and Search: The Threat Intel Positioning
December 24, 2015
The Dark Web is out there. Not surprisingly, there are a number of companies indexing Dark Web content. One of these firms is Digital Shadows. I learned in “Cyber Threat Intelligence and the Market of One” that search and retrieval has a new suit of clothes. The write up states:
Cyber situational awareness shifts from only delivering generic threat intelligence that informs, to also delivering specific information to defend against adversaries launching targeted attacks against an organization or individual(s) within an organization. Cyber situational awareness brings together all the information that an organization possesses about itself such as its people, risk posture, attack surface, entire digital footprint and digital shadow (a subset of a digital footprint that consists of exposed personal, technical or organizational information that is often highly confidential, sensitive or proprietary). Information is gathered by examining millions of social sites, cloud-based file sharing sites and other points of compromise across a multi-lingual, global environment spanning the visible, dark and deep web.
The approach seems to echo the Palantir “platform” approach. Palantir, one must not forget, is a 2015 version of the Autonomy platform. The notion is that content is acquired, federated, and made useful via outputs and user friendly controls.
What’s interesting is that Digital Shadows indexes content and provides a search system to authorized users. Commercial access is available via tie up in the UK.
My point is that search is alive and well. The positioning of search and retrieval is undergoing some fitting and tucking. There are new terms, new rationale for business cases (fear is workable today), and new players. Under the surface are crawlers, indexes, and search functions.
The death of search may be news to the new players like Digital Shadows, Palantir, and Recorded Future, among numerous other shape shifters.
Stephen E Arnold, December 24, 2015
Gibiru Compromised?
December 22, 2015
I assume, gentle reader, that you are aware of the anonymizing search system called Gibiru. Today (December 22, 2015) I received this notification when I attempted to run a query about Palantir on this search system:
The Kaspersky information link is a 404. I located no substantive information about this possible issue when I poked around online. I had in my files a link to https://anonymous-gibiru.com/ which did not trigger the malicious file warning.
Stephen E Arnold, December 22, 2015
Search Vendors Under Pressure: Welcome to 2016
December 21, 2015
I read ”Silicon Valley’s Cash Party Is Coming to an End.” What took so long? I suppose reality is less fun than fantasy. Why watch a science documentary when one can get lost in Netflix binging.
The write up reports:
Based on interviews with about two dozen venture capitalists and tech investors, 2016 is shaping up to be a year of reckoning for scores of technology start-ups that have yet to prove out their business models and equally challenging for those that raised money at unjustifiably high prices.
Forget the unicorns. There are some enterprise search outfits which have ingested millions of dollars, have convinced investors that big revenue or an HP-Autonomy scale buy out is just around the corner, and proprietary technology or consulting plus open source will produce gushers of organic revenue. Other vendors have tapped their moms, their nest eggs, and angels who believe in fairies.
I am not there is a General Leia Organa to fight Star Wars: The Revenue Battle for most vendors of search and content processing. Bummer. Despite the lack of media coverage for search and content processing vendors, the number of companies pitching information access is hefty. I track about 200 outfits, but many of these are unknown either because they don’t want to be visible or lack any substantive “newsy” magnetism.
My hunch is that this article suggests that 2016 may be different from the free money era the articles suggests is ending. In 2016, my view is that many vendors will find themselves in a modest tussle with their stakeholders. I worked through some of the search and content processing companies taking cash from folks with deep pockets often filled with other people’s money. (Note that investments totals come from Crunchbase). Here’s a list of search and content processing vendors who may face stakeholder and investor pressure. The more more ingested, the greater the interest investors may have in getting a return:
- Antidot, $3 million
- Attensity, $90 million
- Attivio, $71 million
- BA Insight, $14 million
- Connotate, $12 million
- Coveo, $69 million
- Digital Reasoning, $28 million
- Elastic (formerly Elasticsearch), $104 million
- Lucidworks, $53 million
- MarkLogic, $175 million
- Perfect Search, $4 million
- Palantir, $1.7 billion
- Recommind, $22 million
- Sinequa, $5 million
- Sophia Ambiance, $5 million
- X1, $12 million.
Then there are the acquired search systems which been acquired. One assumes these deals will have to produce sustainable revenues in some form:
- Hewlett Packard with Autonomy
- IBM with Vivisimo
- Dassault Systèmes with Exalead
- Lexmark with Brainware and ISYS Search
- Microsoft with Fast Search
- OpenText with BASIS, BRS, Fulcrum, and Nstein
- Oracle with Endeca, InQuira, and Rightnow
- Thomson Reuters with Solcara
Are there sufficient prospects to generate deals large enough to keep these outfits afloat?
There are search and content processing vendors competing for sales with free and open source options and the vendors with proprietary software:
- Ami Albert
- Content Analyst
- Concept Searching
- dtSearch
- EasyAsk
- Exorbyte
- Fabasoft Mindbreeze
- Funnelback
- IHS Goldfire
- SLI Systems
- Smartlogic
- Sprylogics
- SurfRay
- Thunderstone
- WCC Elise
- Zaizi
These search vendors plus many smaller outfits like Intrafind and Srch2 have to find a way to close deals to avoid the fate of Arikus, Convera, Delphes, Dieselpoint, Entopia, Hakia, Kartoo, NuTech Search, and Siderean Software, among others.
Despite the lack of coverage from mid tier consultants and the “real” journalists, the information access sector is moving along. In fact, when one looks at the software options, search and content processing vendors are easily found.
The problem for 2016 will be making sales, generating sustainable revenues, and paying back stakeholders. For many of these companies, the new year will be one which sees a number of outfits going dark. A few will thrive.
Darned exciting times in findability.
Stephen E Arnold, December 21, 2015
Plentiful, Presaging Prognostications
December 19, 2015
I read a roll up type article. “Industry Speaks: Top 33 Big Data Predictions for 2016” presents a fulsome suite of forecasts about 2016’s technology trends. If you are a fan of the race track tout approach to winners, you will want to print out this article and keep it with you.
I would love to comment on each prediction, but that, gentle reader, is a lot of work. I would prefer to return to my analysis of Palantir.
I did circle three of the predictions which I found somewhat intriguing. My hope is that you will want to dig deeply into the other 30 future forward conjectures. Here we go:
- Big Data will die. My hunch is that one would have to kill off the PR spouting spawn of marketing and sales departments before the monster of Big Data is tamed. Nice effort, bold prediction. My view is that it is pretty loco given the present environment.
- Companies will hire chief insight officers. Wow. My view is that folks struggling to deliver revenues will change their titles. I am not sure that human resources will work hand in glove with senior executives to hire a new person to be in charge of “insight.” I thought business intelligence software delivered this insight stuff.
- Spark will kill Hadoop. Interesting. I assume I was incorrect in thinking that Hadoop could be thought of as a variant of Google’s really old MapReduce technology. Hadoop is a bit of a challenge, but “killing” seems a bit of a stretch.
For the other 30 previsons, check out the original. Amazing stuff. Most of the horoscopes are like newspaper horoscopes; that is, data free.
Stephen E Arnold, December 19, 2015
Has Enterprise Search Drowned in a Data Lake?
December 6, 2015
I had a phone conversation with a person who unluckily resides in a suburb of New York City. Apparently the long commute allows my contact to think big thoughts and formulate even bigger questions. He asked me, “What’s going to happen to enterprise search?”
I thought this was a C minus questions, but New Yorkers only formulate A plus questions. I changed the subject to the new Chick Fil-A on Sixth. After the call, I jotted down some thoughts about enterprise search.
Here for your contemplation are five of my three comments which consumed three legal pad sheets. I also write small.
Enterprise Search Is Week Old Celery
In the late 1990s when the Verity hype machine was rolling and the Alphabet boys were formulating big thoughts about search, enterprise search was the hot ticket. For some techno cravers, enterprise search was the Alpha and Omega. If information is digital, finding an item of information was the thrill ride ending in a fluffy pile of money. A few folks made some money, but the majority of the outfits jumping into search either sold out or ended up turning off the lights. Today, enterprise search is a utility and the best approach is to use an open source solution. There are some proprietary systems out there, but the appeal of open source is tough to resist. Remember. Search is a utility, not a game changer for many organizations. Good enough tramples over precision, recall, and relevance.
New Buzzwords and the Same Old Tune
Hot companies today do not pound their electric guitar with the chords in findability. Take an outfit like Palantir. It is a search and information access outfit, but the company avoids the spotlight, positions its technology packages as super stealthy magic insight machines. Palantir likes analytics, visualizations, and similar next generation streamlined tangerine colored outputs. Many of the companies profiled in my monograph Cyberosint are, at their core, search systems. But “search” is tucked into a corner, and the amplified functions like fancy math, real time processing, and smart software dominate. From my point of view, these systems are search repackaged and enhanced for today’s procurement professionals. That’s okay. But search is still search no matter what the “visionaries” suggest. Many systems are enterprise search wrapped in new sheet music. The notes are the same.
Big Data
I find the Big Data theme interesting. The idea of processing petabytes of data in a blink is future forward. The problem is that the way statistical procedures operate is to sidestep analyzing every single item. I can examine a grocery list of 10 items, but I struggle when presented with a real time updating of that list with trillions of data points a second. The reality of Big Data is that it has been around. A monk faced with copying two books in a couple of days has an intractable Big Data problem. The love of Hadoop and its extended family of data management tools does not bring the black sheep of the information family into the party room. Big Data requires pesky folks who have degrees in statistics or who have spent their youth absorbed in Mathematica, MatLab, SPSS, or SAS. Bummer. Enterprise search systems can choke on modest data. Big Data kills some systems dead like a wasp sprayed with Raid.
Real Time
For a client in the UK, I had to dig into the notion of real time. Guess what the goslings found. There was not one type of real time information system. I believe there were seven distinct types of real time information. Each type has separate cost and complexity challenges. The most expensive systems were the ones charged with processing financial transactions in milliseconds. Real time for a Web site might mean anything from every 10 second or every week or so. Real time is tough because no matter what technologies are used to speed up computer activities, the dark shadow of latency falls. When data arrive which are malformed, the real time system returns incomplete outputs. Yikes. Incomplete? Yep, missing info. Real time is easy to say, but tough to deliver at a price an average Fortune 1000 company can afford or one of the essential US or UK government agencies can afford. Speed means lots of money. Enterprise search systems usually struggle with the real time thing.
Automatic, Smart Indexing, Outputs, Whatever
I know the artificial intelligence, cognitive approach to information is a mini megatrend. Unfortunately when folks look closely at these systems, there remains a need for slug like humans to maintain dictionaries, inspect outputs and tune algorithms, and “add value” when a pesky third party cooks up a new term, phrase, or code. Talk about smart software does not implement useful smart software. The idea is as appealing today as it was when Fulcrum in Ottawa pitched its indexing approach or when iPhrase talked about its smart system. I am okay with talk as long as the speakers acknowledge perpetual and include in the budget the humans who have to keep these motion Rube Goldberg confections on point. Humans are not very good indexers. Automated indexing systems are not very good indexers. The idea is, of course, that good enough is good enough. Sorry. Work remains for the programmers. The marketers just talk about the magic of smart systems. Licensees expect the systems to work, which is an annoying characteristic of some licensees and users.
Wrap Up
Poor enterprise search. Relegated to utility status. Wrapped up in marketing salami. Celebrated by marketers who want to binge watch Parks and Recreation.
Enterprise search. You are still around, just demoted. The future? Good enough. Invest in hyper marketing and seek markets which do not have a firm grasp of search and retrieval. Soldier on. There are many streaming videos to watch if you hit the right combination on the digital slot machine.
Stephen E Arnold, December 6. 2015
Another Categorical Affirmative: Nobody Wants to Invest in Search
October 8, 2015
Gentle readers, I read “Autonomy Poisoned the Well for Businesses Seeking VC Cash.” Keep in mind that I am capturing information which appeared in a UK publication. I find this type of essay interesting and entertaining. Will you? Beats me. One thing is certain. This topic will not be fodder for the LinkedIn discussion groups, the marketers hawking search and retrieval at conferences to several dozen fellow travelers, or in consultant reports promoting the almost unknown laborers in the information access vineyards.
Why not?
The problem with search reaches back a few years, but I will add a bit of historical commentary after I highlight what strikes me as the main point of the write up:
Nobody wants to invest in enterprise search, says startup head. Patrick White, Synata
Many enterprise search systems are a bit like the USS United States, once the slickest ocean liner in the world. The ship looks like a ship, but the effort involved in making it seaworthy is going to be project with a hefty price tag. Implementing enterprise search solutions are similar to this type of ocean-going effort.
There you go. “Nobody.” A categorical in the “category” of logic like “All men are mortal.” Remarkable because outfits like Attivio, Coveo, and Digital Reasoning, among others have received hefty injections of venture capital in recent memory.
The write up makes this interesting point:
“I think Autonomy really messed up [the space]”, and when investors hear ‘enterprise search for the cloud’ it “scares the crap out of them”, he added. “Autonomy has poisoned the well for search companies.” However, White added that Autonomy was just the most high profile example of cases that have scared off investors. “It is unfair just to blame Autonomy. Most VCs have at least one enterprise search in their portfolio. So VCs tend to be skittish about it,” he [added.
I am not sure I agree. Before there was Autonomy, there was Fulcrum Technologies. The company’s marketing literature is a fresh today as it was in the 1990s. The company was up, down, bought, and merged. The story of Fulcrum, at least up to 2009 or so is available at this link.
The hot and cold nature of search and content processing may be traced through the adventures of Convera (formerly Excalibur Technologies) and its relationships with Intel and the NBA, Delphes (a Canadian flame out), Entopia (a we can do it all), and, of course, Fast Search & Transfer.
Now Fast Search, like most old school search technology, is very much with us. For a dose of excitement one can have Search Technologies (founded by some Convera wizards) implement Fast Search (now owned by Microsoft).
Where Are the Former Big Six in Enterprise Search Vendors: 2004 and 2015
Autonomy, now owned by HP and mired in litigation over allegations of financial fraud
Convera, after struggles with Intel and NBA engagements, portions of the company were sold off. Essentially out of business. Alums are consultants.
Endeca, owned by Oracle and sold as an eCommerce and business intelligence service. Oracle gives away its own enterprise search system.
Exalead, owned by Dassault Systèmes and now marketed as a product component system. No visibility in the US.
Fast Search, owned by Microsoft and still available as a utility for SharePoint. The technology dates from the late 1990s. Brand is essentially low profiled at this time.
Verity, Autonomy purchased Verity and used its customer list for upsales and used the K2 technology as part of the sprawling IDOL suite.
Fast Search reported revenues which after an investigation and court procedure were found to be a bit enthusiastic. The founder of Fast Search was the subject of the Norwegian authorities’ attention. You can check out the news reports about the prohibition on work and the sentence handed down for the issues the authorities concluded warranted a slap on the wrist and a tap on the head.
The story of enterprise search has been efforts—sometimes Herculean—to sell information access companies. When a company sells like Vivisimo for about one year’s revenues or an estimated $20 million, there is a sense of getting that mythic task accomplished. IBM, like most of the other acquirers of search technology, try valiantly to convert a utility into something with revenue lift. As I watch the evolution of the lucky exits, my overall impression is that the purchasers realize that search is a utility function. Search can generate consulting and engineering fees, but the customers want more.
That realization leads to the wild and crazy hyper marketing for products like Hewlett Packard’s cloud version of Autonomy’s IDOL and DRE technology or IBM’s embrace of open source search and the wisdom of wrapping that core with functions.
Enterprise search, therefore, is alive and well within applications or solutions that are more directly related to something that speaks to senior managers; namely, making sales and reducing costs.
What’s the cost of making sure the controls for an enterprise search system are working and doing the job the licensee wants done?
The problem is the credit card debt load which Googlers explained quite clearly. Technology outfits, particularly information access players, need more money than it is possible for most firms to generate. This contributes to the crazy flips from search to police analysis, from looking up an entry in a data base to an assertion that customer support is enabled, hunting for an article in this blog is now real time, active business intelligence, or indexing by proper noun like White House morphs into natural language understanding of unstructured text.
Investments are flowing to firms which could be easily positioned as old school search and retrieval operations. Consider Lexmark, a former unit of IBM, and an employer of note not far from my pond filled with mine run off in Kentucky. The company, like Hewlett Packard, wants to find a way to replace its traditional business which was not working as planned as a unit of IBM. Lexmark bought Brainware, a company with patents on trigram methods and a good business for processing content related to legal matters. Lexmark is doing its best to make that into a Trump scale back office content processing business. Lexmark then bought a technology dating from the 1980s (ISYS Search Software once officed in Crow’s Nest I believe) and has made search a cornerstone of the Lexmark next generation health care money spinning machine. Oracle has a number of search properties. Most of these are unknown to Oracle DBAs; for example, Artificial Linguistics, TripleHop, InQuira’s shotgun NLP technology, etc. The point is that the “brands” have not had enough magnetism to pull revenues on a stand alone basis.
Successes measured in investment dollars is not revenue. Palantir is, in effect, a search and retrieval outfit packaged as a super stealthy smart intelligence system. Recorded Future, funded by Google and In-Q-Tel, is doing a bang up job with specialized content processing. There are, remember, search and retrieval companies.
The money in search appears to be made in these plays:
- The Fast Search model. Short cuts until an investigator puts a stop to the activities.
- Creating a company and then selling it to a larger firm with a firm conviction that it can turn search into a big time money machine
- Buying a search vendor to get its customers and opportunities to sell other enterprise software to those customers
- Creating a super technology play and going after venture funding until a convenient time arrives to cash out
- Pursue a dream for intelligent software and survive on research grants.
This list does not exhaust what is possible. There are me-too plays. There are mobile niche plays. There are apps which are thinly disguised selective dissemination of information services.
The point is that Autonomy is a member of the search and retrieval club. The company’s revenues came from two principal sources:
- Autonomy bought companies like Verity and video indexing and management vendor Virage and then sold other products to these firm’s clients and incorporated some of the acquired technology into products and services which allowed Autonomy to enter a new market. Remember Autonomy and enhanced video ads?
- Autonomy managed well. If one takes the time to speak with former Autonomy sales professionals, the message is that life was demanding. Sales professionals including partners had to produce revenue or some face time with the delightful Dr. Michael Lynch or other senior Autonomy executives was arranged.
That’s it. Upselling and intense management for revenues. Hewlett Packard was surprised at the simplicity of the Autonomy model and apparently uncomfortable with the management policies and procedures that Autonomy had been using in highly visible activities for more than a decade as a publicly traded company.
Perhaps some sources of funding will disagree with my view of Autonomy. That is definitely okay. I am retired. My house is paid for. I have no charming children in a private school or university.
The focus should be on what the method for generating revenue is. The technology is of secondary importance. When IBM uses “good enough” open source search, there is a message there, gentle reader. Why reinvent the wheel?
The trick is to ask the right questions. If one does not ask the right questions, the person doing the querying is likely to draw incorrect conclusions and make mistakes. Where does the responsibility rest? When one makes a bad decision?
The other point of interest should be making sales. Stated in different terms, the key question for a search vendor, regardless of camouflage, what problem are you solving? Then ask, “Will people pay money for this solution?”
If the search vendor cannot or will not answer these questions and provide data to be verified, the questioner runs the risk of taking the USS United States for a cruise as soon as you have refurbed the ship, made it seaworthy, and hired a crew.
The enterprise search sector is guilty of making a utility function appear to be a solution to business uncertainty. Why? To make sales. Caveat emptor.
Stephen E Arnold, October 8, 2015
A New Wave of Old School BI Outfits Are Agile, Maybe Juicy
September 27, 2015
The mid tier outfit Forrester has released another report about enterprise business intelligence platforms” for the third quarter of 2015. These reports cost about $2,500, so you know the information is red hot, spot in, and objective. Always objective. in the write up “The Forrester Wave: Agile Business Intelligence Platforms 2015”, the report is described as “juicy.” Imagine. Juicy applied to IBM, Microsoft, and Oracle. Let me refresh your memory of juicy’s official definition:
1: having much juice : succulent
2: rewarding or profitable especially financially : fat <juicy contract> <a juicy dramatic role>
3a : rich in interest : colorful <juicy details>
b : sensational, racy <a juicy scandal>
c : full of vitality : lusty
I am not sure mid tier consulting firms’ reports are “rewarding or profitable especially financially” for the reader. At a couple of thousand per authorized copy of the report, the mid tier firms are likely to be drenched in juiciness. Will this report be lusty, sensational, colorful, and succulent? Nah. This is marketing pulp, gentle reader.
Which are the companies which make the cut? According to this write up, there are a baker’s dozen of agile, BI vendors:
- Birst
- GoodData
- IBM
- Information Builders
- Microsoft
- MicroStrategy
- Oracle
- Panorama Software
- Qlik
- SAP
- SAS
- Tableau Software
- TIBCO Software.
Scanning this list, I wonder how “agile” IBM, Microsoft, Oracle, SAP, and SAS really are. I know that TIBCO acquired some nifty technology for its analytics functions, and that the founders of Spotfire have moved on to even more interesting analytics at their new company, funded in part by Google and In-Q-Tel. The other firms are ones which have run around the BI bases for years and may have a touch of arthritis; for instance, Information Builders which kicked off its career 1975. Qlik was founded in 1993. MicroStrategy flipped on its lights in 1989 and spawned at least one outfit (Clarabridge) which strikes me as slightly more agile than the mother ship. Tableau, now a publicly traded outfit, hung out its shingle in 2003.
GoodData may be the most spry among this group, not because it was founded in 2007, but because the firm landed another $25 million in funding in 2014.
According to the blurb about the report, each of these companies are agile because of several special features each of these vendors offer their customers. These characteristics are:
First, these 13 vendors’ products allow their business users to be self sufficient. I am not sure I agree, that SAS stuff requires a person to be SAS-sy, which means able to navigate the companies’ programming methods with some skill. IBM, Microsoft, and Oracle provide many different ways to skin the business intelligence cat. In my opinion, these companies’ business intelligence technology require that the business user have the equivalent of a fighter jet maintenance crew to assist them on the flights into analysis and visualization.
Second, each company generates knock out visualizations. My thought is that for zippy visualizations, more specialized tools are required. The companies highlighted in this report can deliver slides and graphs which are niftier than those in Excel, but far short of the Hollywood style outputs which come from Palantir and Recorded Future, among other firms not included in the agile list.
Third, each of the 13 companies offers its licensees and customers options and additional features. This is definitely a must have function. Most of the firms in the list of agile BI companies sells services. Some have partners, lots of partners. The business model may be less to be agile and more to sell billable work, but that’s okay. I am not sure inking a six figure services contract delivers agility.
I assume the complete $2,500 report will become available from the companies listed in the report. For now, think agility. Think IBM, Microsoft, and Oracle, along with the 10 other companies.
Remember, these are 13 juicy and agile outfits. Remarkable. Juicy.
Stephen E Arnold, September 27, 2015
Quote to Note: Confluent
August 20, 2015
I read “Meet Confluent, The Big-Data Startup That Has Silicon Valley Buzzing.” Confluent can keep “he data flowing at some of the biggest and most information-rich firms in Silicon Valley.” The company’s Web site is http://www.confluent.io/. The company uses Apache Kafka to deliver its value to customers.
Here’s the passage i noted:
Experts suggest Confluent’s revenue could approach $10 million next year and pass $50 million in 2017. The company could echo the recent success of another open-source darling, Docker, which has turned record adoption of its computing tools called “containers” into a growing enterprise suite and a $1 billion valuation. Confluent is likely worth about one-sixth that today but not for long. “Every person we hire uncovers millions of dollars in sales,” says early investor Eric Vishria of Benchmark. “There’s real potential [for Confluent] to be an enterprise phenomenon.”
I noted the congruence of Docker and Confluence. I enjoyed the word “every”. Categorical affirmatives are thrilling. I liked also “phenomenon.” The article’s omission of a reference to Palantir surprised me.
Nevertheless, I have a question: “Has another baby unicorn been birthed?” According to Crunchbase, the company has raised more than $50 million. With 17 full time employees, Confluent may be hiring. Perhaps some lucid engineers will see the light?
Stephen E Arnold, August 20, 2015
Poor IBM i2: 15 Year Old Company Makes Headlines in Fraud Detection and Big Blue Is Not Mentioned
August 3, 2015
Before IBM purchased i2 Ltd from an investment outfit, I did some work for Mike Hunter, one of the founders of i2 Ltd. i2 is not a household name. The fault lies not with i2’s technology; the fault lies at the feet of IBM.
A bit of history. Back in the 1990s, Hunter was working on an advanced degree in physics at Cambridge University. HIs undergraduate degree was from Manchester University. At about the same time, Michael Lynch, founder of Autonomy and DarkTrace, was a graduate of Cambridge and an early proponent of guided machine learning implemented in the Digital Reasoning Engine or DRE, an influential invention from Lynch’s pre Autonomy student research. Interesting product name: Digital Reasoning Engine. Lynch’s work was influential and triggered some me too approaches in the world of information access and content processing. Examples can be found in the original Fast Search & Transfer enterprise systems and in Recommind’s probabilistic approach, among others.
By 2001, i2 had placed its content processing and analytics systems in most of the NATO alliance countries. There were enough i2 Analyst Workbenches in Washington, DC to cause the Cambridge-based i2 to open an office in Arlington, Virginia.
i2 delivered in the mid 1990s, tools which allowed an analyst to identify people of interest, display relationships among these individuals, and drill down into underlying data to examine surveillance footage or look at text from documents (public and privileged).
IBM has i2 technology, and it also owns the Cybertap technology. The combination allows IBM to deploy for financial institutions a remarkable range of field proven, powerful tools. These tools are mature.
Due to the marketing expertise of IBM, a number of firms looked at what Hunter “invented” and concluded that there were whizzier ways to deliver certain functions. Palantir, for example, focused on Hollywood style visualization, Digital Reasoning emphasized entity extraction, and Haystax stressed insider threat functions. Today there are more than two dozen companies involved in what I call the Hunter-i2 market space.
Some of these have pushed in important new directions. Three examples of important innovators are: Diffeo, Recorded Future, and Terbium Labs. There are others which I can name, but I will not. You will have to wait until my new Dark Web study becomes available. (If you want to reserve a copy, send an email to benkent2020 at yahoo dot com. The book will run about 250 pages and cost about $100 when available as a PDF.)
The reason I mention i2 is because a recent Wall Street Journal article called “”Spy Tools Come to Wall Street” Print edition for August 3, 2015) and “Spy Software Gets a Second Life on Wall Street” did not. That’s not a surprise because the Murdoch property defines “news” in an interesting way.
The write up profiles a company called Digital Reasoning, which was founded in 2000 by a clever lad from the University of Virginia. I am confident of the academic excellence of the university because my son graduated from this fine institution too.
Digital Reasoning is one of the firms engaged in cognitive computing. I am not sure what this means, but I know IBM is pushing the concept for its fascinating Watson technology, which can create recipes and cure cancer. I am not sure about generating a profit, but that’s another issue associated with the cognitive computing “revolution.”
I learned:
In pitching prospective clients, Digital Reasoning often shows a demonstration of how its system respo9nded when it was fed 500,000 emails related to the Enron scandal made available by the Federal Energy Regulatory Commission. After being “taught” some key concepts about compliance, the Synthesys program identified dozens of suspicious emails in which participants were using language that suggested attempts to conceal or destroy information.
Interesting. I would suggest that the Digital Reasoning approach is 15 years old; that is, only marginally newer than the i2 system. Digital Reasoning lacks the functionality of Cybertap. Furthermore, companies like Diffeo, Recorded Future, and Terbium incorporate sophisticated predictive methods which operate in an environment of real time information flows. The idea is that looking at an archive is interesting and useful to an attorney or investigator looking backwards. However, the focus for many financial firms is on what is happening “now.”
The Wall Street Journal story reminds me of the third party descriptions of Autonomy’s mid 1990s technology. Those who fail to understand the quantity of content preparation and manual, subject matter expert effort required to obtain high value outputs are watching smoke, not investigating the fire.
For organizations looking for next generation technology which is and has been working for several years, one must push beyond the Palantir valuation and look to the value of innovative systems and methods.
For a starter, check out Diffeo, Recorded Future, and Terbium Labs. Please, push IBM to exert some effort to explain the i2-Cybertap capabilities. I tip my hat to the PR firm which may have synthesized some information for a story that is likely to make the investors’ hearts race this fine day.
Stephen E Arnold, August 3, 2015
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