The legal analytics platform Lex Machina, which is owned by LexisNexis, has been steadily expanding its coverage into new practice areas, and today has added insurance litigation.

The new module provides analytics for more than 92,200 cases pending in federal court since 2009 that involve disputes between an insurer and a policyholder, a beneficiary, or another insurer asserting the rights of a policyholder.

These insurance cases make up the third-largest case set on the Lex Machina platform, the company says, with court-awarded damages totaling nearly $2.8 billion.

The module covers a variety of policy types, including homeowners, automobile, life, commercial liability, professional liability, uninsured/underinsured motorists, health, disability income, and others. It does not cover Medicare, Social Security disability and ERISA claims. It includes only insurance cases (including class actions) that were litigated  in federal district court, and in which parties that reside in different states dispute claims involving more than $75,000.

With its expansion into insurance litigation, Lex Machina now covers 10 practice areas: patent, copyright, trademark, antitrust, securities, employment, commercial, product liability, federal bankruptcy appeals, and insurance litigation.

In the process of creating this module, Lex Machina added 50 insurance-specific case tags and annotations to better enable users to find relevant cases and filter out others. Lawyers can use these analytics to see the track records of opposing counsel and parties, the experience and behaviors of judges, and key factors about cases, such as case timing, findings and damages.

Among the 50 new insurance-related case tags:

  • Forty-two new findings, including: Duty to Defend, Duty to Indemnify, Bad Faith, Insurer Negligence, Policy Exclusion, Failure to Pay Premium, Insured Fraud, Unjust Enrichment, and Estoppel/ Waiver.
  • Seven insurance damage types: Contract Damages, Restitution, Tort Damages, Emotional Distress Damages, Enhanced Damages,Punitive Damages and Approved Class Action Settlement.
  • Two Insurance Remedies: Rescission and Reformation.

With the launch of its insurance module, Lex Machina has already uncovered interesting historical insights into insurance litigation, including:

Webcast on Insurance Analytics

For anyone interested in learning more about the insurance litigation module, Lex Machina is presenting a free webcast Thursday, Aug. 9, at 1 p.m. Eastern time. You can learn more and register here.

Ever since LexisNexis acquired the legal research startup Ravel last June, its plan has been to integrate Ravel’s caselaw visualization technology and data analytics into Lexis Advance. Earlier this year, I published a preview of the integration of the visualization technology. Today, LexisNexis is formally launching that integration and beginning to roll it out to customers.

The name given to this new tool within Lexis Advance is Ravel View. It looks and functions very much like Ravel did as a standalone platform, but with one significant difference — the Ravel visualizations now include Shepard’s citation information.

Ravel’s concept all along has been to display search results visually, along a cluster map that shows the relationships among cases and their relative importance to each other. This visual depiction provides researchers with a quicker understanding of the overall landscape of relevant cases and also helps identify the cases that are most important.

In the standard search-results view, click the icon in the upper right corner to switch to Ravel View.

Now in Lexis Advance, when a user conducts a query, the default results page will remain the traditional list of relevant cases. But the user will be able to click an icon in the upper rate of the screen to toggle the visual view, which displays the cluster map on the left side of the screen and the list of cases on the right.

Ravel View shows search results visually, with cases represented by circles on a cluster map.

Ravel View maps the top 75 cases relevant to the user’s search. Each case is represented as a circle, with lines between circles showing the citations between cases. This visualization shows:

  • Citation frequency. The bigger the circle, the more frequently that case has been cited by other cases, a measure of its importance.
  • Chronology. Ravel View maps cases across time, revealing trends and patterns in the development of precedent.
  • Jurisdiction. The vertical axis shows the Supreme Court at the top, followed by federal and state courts below. This shows the governing relationships among cases based on their court hierarchy.
  • Relevance. The higher a circle appears within each jurisdiction band, the more relevant the case is to the search.

When a user clicks on any circle, Ravel View displays the case name and citation relationships, and elevates the case to the top of the search results in the right panel so users can read the full  description.

Hover over a line connecting two cases to show the Shepard’s treatment.

The incorporation of Shepard’s comes by way of the lines connecting each case. The lines are colored green, yellow or red to correlate to Shepard’s signal colors for positive and negative treatments. By hovering over a line, the user can display the language from the citing case that illustrates why Shepard’s assigned that treatment.

Ravel View will become available to every Lexis Advance subscriber on a phased-in basis over the next couple of weeks. By mid-July, it should be available to everyone.

Ravel CEO Daniel Lewis, who conceived the visual legal research platform while a second-year student at Stanford Law School, told me earlier this week that he is particularly excited about the integration of the Shepard’s citator information into Ravel’s visualizations.

“The highlight is the cool combination of taking the technology we had and adding it to the content and expertise that Lexis has to create this mashup,” he said.

Still to come is the integration of Ravel’s analytics into Lexis Advance. Ravel’s suite of analytics included court, judge and case analytics. The first of those integrations will come out over the next couple months, he said, in the form of a new product on the Lexis platform. That effort is being led by Ravel cofounder Nick Reed.

For now, Ravel continues to operate as a standalone platform. But once the integration is complete, Ravel’s customers will be transitioned to Lexis, Lewis said. “The things you liked in Ravel you will be able to do better in Lexis,” he said.

Daniel Lewis was just in his second year at Stanford Law School when he had an idea for a different way to do legal research, as I recounted in this 2014 ABA Journal article. His idea was to display search results visually, along a cluster map that shows the relationships among cases and their relative importance to each other. Shortly after he graduated in 2012, he and classmate Nicholas Reed had launched the legal research platform derived from his idea, Ravel Law. Last June, five years after its founding, Ravel was acquired by legal research giant LexisNexis.

By that time, Ravel had also developed a suite of analytics that included court analytics, judge analytics and case analytics. At the time of the acquisition, Jeff Pfeifer, VP of product management for LexisNexis, told me that the acquisition — which followed the acquisition of another legal analytics company, Lex Machina — was part of the company’s broader vision “to create the data-driven lawyer of the future.”

From the outset, the plan was to integrate Ravel’s data visualization technology and data analytics into Lexis Advance and other Lexis products, and to bring those integrations to market starting within the first quarter of 2018.

They are, it seems, right on schedule. At Legalweek in New York this week, I met with Pfeifer and Lewis and saw a preview of the integration of Ravel’s visualization technology into Lexis Advance. The integration is scheduled to be released early in March, said Pfeifer, who reaffirmed the company’s commitment to enabling “data-driven law.”

Preview of Integration

The two images that follow are a preview of this integration.

In the first image, you see what will be the default view after a user conducts a search. This looks much like it would look today, but with one notable change. The circle to the right of each result is what Pfeifer jokingly called the “Shepard’s donut.” It uses the colors of Shepard’s signal indicators to give the user a quick visual overview of how the case has been treated in subsequent citations.

By clicking View Mode in the upper right corner of the screen, the user can switch over to the search visualization mode based on the Ravel integration. This will look familiar to anyone who has ever seen Ravel. It uses the same cluster map of larger and smaller bubbles showing connections among cases and relative importance of cases, all arranged along a timeline.

One notable addition to the visualization is Shepard’s citation data. Now, the lines connecting cases include a colored dot, with the dot reflecting the Shepard’s signal indicator. Click on the dot to bring up a selection of text from the citing case that shows the basis for the Shepard’s treatment.

Analytics on Experts

As I said, the visualization will become available in Lexis Advance in March. In a second phase, scheduled for May, Ravel’s analytics tools will be incorporated into Lexis Advance. This will allow Ravel’s court, judge and case analytics to be used within Advance, and will extend the reach of those analytics to a broader selection of state, as well as federal, trial courts.

The May release will also use Ravel’s analytics to provide a greater depth of information about expert witnesses.  expand the analytics to include expert witnesses. A current product, LexisNexis Litigation Profile Suite, will be replaced by an updated product with a new name — as yet to be decided — that marries Ravel’s analytics with the existing profiles to provide more information on experts, such as how often they have been challenged, how often they testify, and more. The new Profile Suite product will also have more in-depth analytics on parties, judges and neutrals.

(Profile Suite will continue to be available for current customers who prefer not to move to the new product, Pfeifer said.)

Harvard Case Data

Before its acquisition by LexisNexis, Ravel had embarked on a project with Harvard Law School to digitize all U.S. case law. As I reported at the time of the acquisition, both Harvard and LexisNexis committed to completing that project, carried out under the auspices of the Harvard Library Innovation Lab.

The scanning of all those cases wrapped up nearly a year ago, but the final clean-up and digitization was just completed, Pfeifer and Lewis told me. Those cases have now been added to the Lexis Advance database. The total collection from Harvard was 5-7 million documents, and a “few hundred thousand” of them were cases not previously included in Lexis, Pfeifer said. That brought the number of case documents in Lexis Advance from 13.5 million to nearly 14 million.

In addition, later this year, Lexis Advance will be adding PDFs of all the cases from the Harvard collection. These include cases from before the American Revolution up to 2016.

Part of the agreement between Ravel and Harvard was that access to these cases would remain free to everyone. After the acquisition, LexisNexis and Harvard confirmed that commitment. Pfeifer and Lewis said this week that the Ravel website will be maintained as the primary site for the public to access those cases.


When LexisNexis acquired the legal analytics platform Lex Machina in November 2015, the the plan was to integrate Lex Machina’s analytics into various LexisNexis products and, in particular, its Lexis Advance legal research platform. Last January, it took the first step in that direction when it integrated judge analytics into Lexis Advance, and later in the year it added integration for law firm analytics.

Yesterday LexisNexis rolled out the third such integration, attorney analytics. Now, when Lexis Advance users are viewing full-text cases, they can click on the names of the attorneys involved in the case and view summary charts showing data about the attorney, such as the attorney’s case-filing history.

This works for the practice areas currently covered by Lex Machina: patent, copyright, trademark, antitrust, securities, employment, commercial, product liability and federal bankruptcy appeals.

From that summary page, Lexis Advance users who also have a subscription to Lex Machina can drill further into the full Lex Machina set of analytics.

(Note that attorneys’ names have been blotted out from these images.)

Some items I’ve been meaning to blog about:

LexPredict open-sources its contract analytics platform. LexPredict, the technology consulting and development company founded by CEO Michael Bommarito and Daniel M. Katz, professor at Chicago Kent College of Law, has announced that it will open source the development of ContraxSuite, its platform for contract and document analytics. Starting Aug. 1, the code base and LexPredict’s public development roadmap will be hosted on Github under a permissive open-source licensing model that will allow organizations to implement and customize their own contract and document analytics. LexPredict will provide support, customization and data services for organizations that need it. As for why they’re doing this, Bommarito and Katz have published a detailed explanation.

A primer on AI in law. Speaking of Dan Katz, I recently came across a primer he’s published on artificial intelligence in law. In six parts spanning 290 slides, Katz provides an accessible introduction to AI for anyone interested in better understanding this burgeoning area of technology.

Alexa, tell me what’s up with Cooley LLP. You can now ask Amazon’s Alexa for updates from the Facebook page of Cooley LLP. Cooley has signed on to be a “skill” with Witlingo, a company that enables enterprises to deliver conversations on voice services. Users will be able to ask Alexa to read posts from Cooley’s Facebook page, share the posts on their walls, and ask that links of the posts be texted to them. To try it, ask Alexa to “enable Cooley LLP.” This brief video demonstrates:

Does ILTACON now overshadow Legaltech New York? At eDJ Blog, Greg Buckles finds that ILTA’s annual convention (which kicks off Aug. 13 in Las Vegas) now surpasses Legaltech in numbers of exhibitors (217 at ILTA compared to 152 at Legaltech) and in numbers of event sponsors (25 at ILTA compared to 13 at Legaltech). “ILTA still tries to be a ‘vendor free’ zone, but 217 sponsors and 39 vendor sessions on the agenda clearly demonstrate the marketing penetration of the event,” he says.

Lee Rosen

Two years as a digital nomad lawyer. For two years, I’ve followed lawyer Lee Rosen as he’s traveled the world while still running his law practice, posting regular updates to Instagram, and I’ve wondered, “How the heck does he do it?” Well, now he’s answered that question.

A new podcast on legal marketing has been launched by the legal marketing firm Good2BSocial. Hosted by Guy Alvarez, the firm’s founder, and Tim Baran, its chief marketing officer, the podcast features guests from inside and outside the legal industry. Episodes so far have covered such topics as niche marketing, law firm CRM, social media ethics, marketing analytics, and more. Subscribe in iTunes or follow on SoundCloud.

ALM treatises now on LexisNexis Digital Library. A new deal between LexisNexis Legal & Professional and ALM puts more than 250 treatises published by ALM on the LexisNexis Digital Library, a service that provides law libraries with ebook lending capabilities for more than 3,000 titles. The deal adds titles from Law Journal Press, The National Underwriter Co. and publications such as The Legal Intelligencer, New York Law Journal, New Jersey Law Journal and more. Read more here.

The new employment module includes analytics showing case resolutions.

When LexisNexis acquired the legal analytics platform Lex Machina in November 2015, the plan was to use LexisNexis’s collection of federal and state docket data to expand Lex Machina’s analytics beyond its original area of intellectual property. Since then, it has been adding practice areas at a regular clip, starting with securities last July, antitrust in November, and commercial litigation last month.

Now comes employment litigation, as Lex Machina today announces an employment litigation module that analyzes data from some 71,000 discrimination, retaliation and harassment cases filed in federal court since 2009. The new module provides the same sorts of analytics as prior modules, offering insights into case timing, resolutions, damages, remedies and findings, as well as information on law firms, parties, judges and venues.

“We decided after the Lexis acquisition that if we wanted to go big we’d have to attack the broad middle of the law,” Owen Byrd, chief evangelist and general counsel at Lex Machina, told me yesterday. “In terms of case count and value to practitioners, we quickly centered on commercial and employment as our first big additions to our offering. Last month, we rolled out commercial. Now rolling out this week is federal employment litigation analytics.”

Analytics show the timing to key events in cases.

The module provides analytics for three types of employment cases, those in which an employee is suing an employer for discrimination, retaliation or harassment. In the fall, Lex Machina will add disabilities and labor relations cases to the module.

Next month, Lex Machina will add a module for bankruptcy cases, Byrd said.

While the underlying analytics are the same, each new module requires the addition of subject-specific tags. Lex Machina says it develops these tags by interviewing practitioners in each area of law to better understand their practice area and use cases. The employment module adds tags related to:

  • Damages. New tags have been added for back pay/lost wages, emotional distress, front pay, liquidated damages, and punitive damages.
  • Findings: New tags have been added for discrimination statues such as Title VII (race/color, religion, national origin, sex/gender), ADEA (age), PDA (pregnancy), §1981/§1983 (equal rights/civil rights violations), USERRA (members of the military), the Equal Pay Act and the Rehabilitation Act. Tags have also been added for hostile work environment/harassment, retaliation, failure to mitigate defense, time barred defense, failure to accommodate, legitimate nondiscriminatory/non-retaliatory reason defense, and failure to exhaust administrative remedies.
  • Remedies: New tags related to remedies are notice posting, promotion and reinstatement.
This shows employment findings by judgment event.

Lex Machina says that the new employment analytics will allow attorneys to answer questions such as:

  • How many times have damages for lost wages been awarded in a federal employment case? What were the specific amounts?
  • What can you know about a law firm sending a demand letter – how real is the threat?
  • Which law firms have the most experience defending Walmart in federal employment cases?
  • How often – and in which cases – have judges in the District of Delaware found a hostile work environment?
  • What are the chances of obtaining a summary judgment order in an employment case from a specific judge?

In demonstrating the module yesterday, Byrd pointed out some interesting findings revealed by the analytics. One is that the law firms generally perceived to be the three dominant firms representing employers in employment cases truly are. Data shows that the firms with the most employment cases are Littler Mendelson, Ogletree Deakins, and Jackson Lewis.

The data also shows that plaintiffs rarely win in employment litigation. Although the analytics do not reveal the outcomes of cases that settle, for those that go to trial, plaintiffs win in just 1 percent of cases, and on summary judgment, plaintiffs win in only a negligible fraction of cases compared to employers.

With regard to remedies, the analytics show that punitive damages were awarded in only 192 employment cases and attorneys’ fees in just 437 cases.

Some other trends revealed by the data:

  • Based on cases filed between Jan. 1, 2009, through June 30, 2017, discrimination lawsuits are by far the most common (87 percent of cases), followed by retaliation (66 percent) and harassment (35 percent).
  • Employment cases often involve overlapping kinds of claims. Discrimination and retaliation claims are combined more than half the time, and the other two combinations occur in about a third of cases.
  • Cases with all three tags comprise just under a quarter of the cases.
  • Top government defendants include local entities such as the City of New York and the Metropolitan Washington Airport Authority, as well as federal organizations such as the U.S. Post Office and Department of Defense.
  • Corporations facing the most employment cases include Walmart, Home Depot, Target, United Parcel Service, Bank of America, and United Airlines.

If you are interested in learning more about this new module, Lex Machina is hosting a free webcast tomorrow, July 13, at noon Eastern time to demonstrate its analytics and discuss some of the trends in employment litigation the analytics reveal. The webcast will be moderated by David Lat, founder and managing editor of Above The Law, and will include David Walton, shareholder at Cozen O’Conner; Patrick DiDomenico, chief knowledge officer at Ogletree, Deakins; and Byrd.

LexisNexis is today announcing the launch of Lexis Answers, a feature that brings artificial intelligence to the Lexis Advance legal research platform. With Lexis Answers, a researcher can ask a natural-language question and get back the single-best answer in the form of what Lexis is calling a Lexis Answer Card.

LexisNexis says that Lexis Answers uses powerful machine learning, cognitive computing and advanced natural language processing technologies to deliver the single best and most authoritative answer, in addition to comprehensive but more precise search results.

“Lexis Answers is designed to help a lawyer get more complete information from a query by parsing the query to understand its intent and then delivering a precise answer to the question that’s been asked,” Jeff Pfeifer, vice president, product management, told me on Friday.

The answer is delivered in the form of an Answer Card, which both provides the answer and links to the specific text within the document that is the source of the answer. In addition, Lexis Answers suggests related topics and concepts to help the researcher expand the search.

Lexis Answers is available to all Lexis Advance subscribers at no extra cost. Users need do nothing to activate it — if the user enters a query in Lexis Advance that is suitable for Lexis Answers, the Answer Card will appear as a query result.

Parsing the User’s Intent

With today’s launch, Lexis Answers works only with questions that fall into one of five common categories: standards of review, burdens of proof, elements of claims, standard legal definitions, and core legal doctrines.

For example, the question, “What is the burden of proof for fraud in New York?” would produce an Answer Card with the specific answer, as well as standard search results and suggestions of related topics.

“Previously we would have run that query as a natural language or Boolean search,” said Pfeifer. “Now we parse the language of the query to identify the user’s intent so we can provide a specific answer.”

Users are not required to enter fully formed questions, Pfeifer said. Rather, the machine learning application parses the query and dynamically mines the underlying data set for the answer. Answers are not pre-processed and stored, but answered in real time.

“Because the user’s query is linguistically dissected as opposed to term-matched, we can present a better answer as well as related terms and concepts,” Pfeifer said. “Instead of dissecting a query, we’re understanding linguistically the intent of the query.”

The machine learning that underlies Lexis Answers has been trained using content from case law and legal dictionaries. Over time, it will be expanded to include additional content.

Related Concepts

For Lexis Answers, Lexis has constructed a Knowledge Graph – a graph of relationships and associated concepts – that helps it present recommendations of related legal concepts. (This is the “see also” section in the image at the top of this post.) In the future, the graph will display related entities, documents and other material.

“The knowledge graph grows and relationships are created over time as additional content is processed by our machine learning algorithms,” Pfeifer said.

I have not yet seen or used Lexis Answers, but as Pfiefer described it to me, it sounded similar to ROSS Intelligence, which has garnered much attention in the past year for its AI-powered legal research. Both Lexis Answers and ROSS use AI to help researchers find the “best” answer based on natural language queries. (I also have not used ROSS, although I’ve asked the company to provide me with access or a demo.) Pfiefer also hasn’t seen ROSS, but he agreed that the two research tools may be similar in that they are both based on machine learning technologies that try to map the intent of the query against a set of trained data.

More AI to Come

Lexis Answers was developed over the last 18 months at LexisNexis’s Raleigh Technology Center, where a team of data scientists, computational linguists, advanced engineering and product management professionals are developing various AI products for lawyers. LexisNexis says that it will be releasing additional AI products throughout this year and beyond.

Future development of Lexis Answers will also benefit from LexisNexis’s recent acquisition of Ravel Law, Pfeifer said. Already, the LexisNexis Raleigh team and Ravel’s development team have started working together and plans are underway to add new question types to Lexis Answers based on Ravel’s court and judge analytics.

“We’re excited about this because it really represents the beginnings of a fairly foundational transformation in the way people query large data sets,” Pfeifer said. “In the past, the focus has been on constructing Boolean searches or using the right keywords. Now, we’re at a pivotal point in interacting with large data sets. The interaction becomes more dialog-like — the interaction will be more like human interaction.”

Lexis Answers is LexisNexis’s first foray into cognitive computing, but Pfeifer said he cares less about labels such as artificial intelligence and machine learning and more about the utility being delivered to the end users.

“The end result for the attorneys should simply be better answers to their questions,” Pfeifer said. “The idea that it has to be a machine-learning application is less relevant than that the user of the machine-learning technology is delivered a better answer.”

The legal analytics company Lex Machina today announced what it is describing as the most ambitious and largest expansion yet of its analytics into a new practice area, commercial litigation.

Since its acquisition in November 2015 by LexisNexis, Lex Machina has been using LexisNexis’s collection of federal and state docket data to expand its analytics platform beyond its original area of intellectual property into other practice areas, adding securities last July and antitrust in November. It plans eventually to cover every federal practice area.

With today’s release, Lex Machina is adding data on 62,000 commercial cases dating back to 2009. Attorneys will be able to use its analytics to obtain insights on case timing, resolutions, findings, damages, , remedies, and also to obtain competitive and strategic intelligence on opposing counsel, law firms, parties, judges, venues, and more.

Lex Machina says that, to meet the needs of commercial litigators, today’s release adds new practice area-specific tags and features, including:

  • Expanded case timing analytics. In addition to the time-related analytics it already had — such as time to dismissal, trial and termination — this new release adds time to permanent injunction and summary judgment.
  • New damages categories. Commercial cases include contract damages, restitution, and other damages, as well as tort compensatory damages and punitive damages.
  • New breach of contract and business tort findings. New tags have been added for contract breach, existence, rescission, and termination, as well as contract defense and unjust enrichment. Business tort findings include conversion, defamation/trade libel, fraud/misrepresentation, misappropriation of trade secrets, negligence, tortious interference, and tort defense.

In announcing today’s news, Lex Machina CEO Josh Becker said the addition of commercial litigation was the company’s most ambitious addition yet because the category transcends so many types of legal practice. Of over 62,000 commercial cases filed since 2009, 80 percent include a breach of contract claim and 57 percent include a business tort claim. Roughly 25 percent of commercial cases meet the definition of an intellectual property, securities or antitrust case, and are coded in PACER as such.

At noon Eastern today, Lex Machina is presenting a webcast about its new commercial litigation analytics: “New Legal Analytics for Commercial Litigation.”

Legal research company Fastcase today announced that Steve Errick, who was most recently vice president and managing director for research information at LexisNexis, will join the company on July 1 as chief operating officer.

Steve Errick

Ed Walters, Fastcase CEO, told me that Errick is being brought on to help lead the growth and expansion of Fastcase, which Walters and Phil Rosenthal, Fastcase’s president, founded in 1999 after leaving their associate positions at the Washington, D.C., law firm Covington & Burling.

“I’m immensely proud of what Phil and I have been able to do to get Fastcase to where it is,” Walters said. “We bootstrapped the company and built a great product. But I feel like there’s a 10-times bigger version of Fastcase that’s waiting to break out. To achieve that, we need to bring in skills that we don’t currently have. We wanted a real veteran, an industry expert, who can help us manage day-to-day effectively at scale.”

Errick will be responsible for executing the company’s strategic vision, developing new editorial products, and developing the company’s organizational structure as the company expands.

Errick is a legal publishing veteran who is well known and well respected in the industry. At LexisNexis, he oversaw the Legal Research Information Product Division, with a $1 billion P&L portfolio. He led development of workflow tools such as Total Patent; Litigation Suite, which included MedMal Navigator; E-book Digital Lending; Lexis for Microsoft Office; and Lexis Practice Advisor; and he shepherded LexisNexis’s acquisition of Law360, Securities Mosaic, and Sheshunoff/AS Pratt Financial Services.

Earlier, he was vice president and general manager of Wolters Kluwer’s CCH Publishing division, publisher of Thomson Reuters’s Foundation Press division, and director of acquisitions of Thomson’s Clark Boardman Callaghan division.

In a press release, Fastcase said that it would begin editorial publishing starting in 2018 to expand the reach of its legal research service. So far, Fastcase content has been limited to primary law — cases, statutes, regulations, court rules and constitutions. It now plans to launch its own imprint of expert treatises, secondary material and journals and to partner with state bar associations to develop state workflow products.

Walters told me that he foresees a new approach to secondary-material publishing, one that taps into Fastcase’s own user data to identify trends and interests and then develops materials in response to those interests. Fastcase users conduct 1 million searches a month, he said, and from that data Fastcase can analyze trends.

“We might see there’s a giant surge of litigation in the Eastern District of Texas, so maybe we’d put together the Eastern District of Texas litigation manual,” Walters said.

In addition to developing secondary material, Walters sees Fastcase growing in two other ways.

One is expanding the kinds of data it has. In addition to court cases, it may also add docket data, for example, or other kinds of data its customers are interested in.

The other growth area is global, he said. “We’re popular in the United States, but people all around the world have the same legal information needs.”

In addition to his work in legal publishing, Errick also runs his own small publishing house, Twelve Tables Press, with a number of law-related titles, and owns a bookstore and cafe in Brandon, Vt., Book and Leaf.