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


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