A legal analytics product being launched today by LexisNexis does something no other analytics product does: It analyzes the language of specific judges’ opinions to identify the cases and arguments each judge finds persuasive.

The new product, Context, also provides analytics on expert witnesses, and may be the most  comprehensive product available for this purpose.

In a way, Context is déjà vu all over again. The original version of these judge analytics was launched by Ravel Law in 2015. After LexisNexis acquired Ravel in June 2017, development pivoted to incorporating Ravel’s tools into the Lexis Advance legal research platform. The first stage of that incorporation came last June, when Lexis Advance integrated Ravel’s case law visualization tools as a product called Ravel View. Today’s launch of Context is the second major step in that integration.

That said, Context is a more powerful analytics tool than the original product, Ravel’s cofounders Nik Reed and Daniel Lewis told me during a call this week. Both now work for Lexis, where Reed is senior director of product and strategy and Lewis is general manager. Both say Context has been made stronger by the far deeper pool of data and more advanced technology available through LexisNexis.

Today’s launch, with judge analytics and expert witness analytics, is the first phase of Context. Future releases will add court analytics, company analytics, and lawyer and law firm analytics.

Judge Analytics

What makes this product unique among litigation analytics tools is that it analyzes the language of court documents. Other litigation analytics products, such as Lex Machina, which is also a LexisNexis product, or Westlaw Edge, are based on analysis of court dockets. Those products can tell you information such as how long a particular type of case is likely to last, how a judge is likely to rule on a particular type of issue, or how other lawyers have fared before a particular judge. Such information is derived from the docket.

Motion outcomes for U.S. District Judge William Alsup.

By contrast, Context analyzes the text of court documents to find language and citations that could prove persuasive to a particular judge. Specifically, it tells you how a judge has ruled on 100 different types of motions and the judges, cases and text the judge most commonly relied on in making those rulings.

Say you are filing a motion for summary judgment. Using Context, you could look up the judge and determine the rate at which that judge grants or denies summary judgment. You could see all of the specific cases in which the judge made these rulings. Then, going deeper, you can see the opinions that the judge most frequently cites in summary judgment cases, and even the specific text from those opinions that the judge most frequently relies on.

Citation analytics show the cases and judges a judge finds persuasive.

With this information, you can tailor your memorandum to fit the judge. You can cite the judges, cases and even passages that you know the judge has relied on in the past and finds persuasive. That is a powerful tool.

Context’s judge analytics cover all federal judges, including appellate judges, and some, but not all, state court judges. Because appellate judges do not rule on litigation motions, motion analytics are not available for them (unless, I presume, they were previously a trial judge). However, citation analytics do work for appellate judges, so you can see for opinions authored by that judge the cases and text they most commonly rely on.

There is no backward time limit to Context’s coverage. If a judge has been on the bench for decades, the entirety of the judge’s output is included in Context’s analytics.

Expert Witnesses

The expert witness analytics released today are a new analytics product not previously offered as part of Ravel’s original set of analytics tools. The reason for that is simple: Ravel did not have data on expert witnesses, but LexisNexis has an extensive set of such data, covering more than 380,000 experts.

For each expert covered by Context, a user can see an overview that provides biographical and experiential information about the expert. For many experts, this includes not only the expert’s current CV, but also prior versions of the CV has it has been presented over the years. The overview also shows whether the expert is typically hired by plaintiffs or defendants, the number of cases per year the expert is engaged in, and the expert’s experience by jurisdiction and areas of law.

A deeper layer provides analytics on Daubert challenges to the expert. Nik Reed calls this a scorecard. For each expert, it shows the challenges by factor — methodology, qualification, relevance or procedural — and then the outcome. As you look at this scorecard, you can view each of the opinions in which the challenge was decided.

Reed says these analytics can be useful both when retaining an expert, to see how that expert has fared historically, and when challenging an opponent’s expert, to see which grounds have been successful in the past in excluding that expert.

These expert analytics cover only federal court challenges, but Reed said state court challenges will be added by the middle of 2019. Also in the works is attorney and firm connections, so that a user can see the specific attorneys and firms to which an expert has been connected.

There are other expert-witness analytics products on the market. Among the most comprehensive is Courtroom Insight, which has its own expert witness analytics and which also is integrated in the Fastcase AI Sandbox. It covers some 100,000 expert witnesses.

Future Development

Reed and Lewis said that the product being launched today is just the beginning. The next module to be added will be court analytics, which will break down the handling of specific types of motions by courts, rather than just specific judges within those courts. These will be similar in concept, but not scope, to the court analytics previously offered by Ravel, which I wrote about here.

After that will come a module providing analytics on companies as litigants, and then a module on lawyers and law firms that will show data such as success rates on particular types of motions and before specific courts or judges. Again, these will be similar to the law firm analytics previously offered by Ravel, which I wrote about here.

This latter module will be useful to researchers not just for litigation strategy, but also for performing competitive analysis and intelligence, Reed and Lewis said.

Pricing and Availability

LexisNexis is offering 30 days of free access to Context to any Lexis Advance subscriber who registers at www.lexisnexis.com/context. The free trial will run from Jan. 2 to Jan. 31, 2019. In addition, LexisNexis is providing free access starting today to all law school faculty, and to all law students who have a Lexis Advance ID starting Jan. 2.

Also starting today, access to Context will be provided to all current customers of Ravel Analytics through its legacy site.

Otherwise, for Lexis Advance customers, Context will be sold as an add-on to their subscription. Subscribers will be able to choose from among different modules. The two products released today will be sold as a single module. The modules will also be sold in packages oriented to either legal research or competitive intelligence.

LexisNexis declined to provide specifics on pricing.

“It’s been exciting for Nik and me personally to not just rebuild this, but to add new bells and whistles and to expand the functionality,” Lewis told me. “We have made it better in meaningful ways.”

What does it mean to practice data-driven law? On this episode of LawNext, I speak with Jeff Pfeifer, the LexisNexis vice president charged with driving overall product strategy for LexisNexis Legal and Professional, North America. Over the past several years, Pfeifer has spearheaded a series of acquisitions and product developments, all with the goal of establishing LexisNexis as the leader in legal analytics and enabling what he calls data-driven law.

Pfeifer oversaw the company’s 2016 acquisitions of legal analytics companies Lex Machina and Intelligize and the 2017 acquisition of Ravel Law. Most recently, Pfeifer led the roll-out of Lexis Analytics, a suite of tools that organizes all of LexisNexis’s major analytics acquisitions and products (as well as a couple new products) into three categories of analytics – litigation, regulatory and transactional. I speak with Jeff about these acquisitions, the launch of Lexis Analytics, and his vision of the data-driven lawyer.

Pfeifer is a 29-year veteran of LexisNexis. Before taking on his current role in 2015 as vice president of product management, he was vice president, primary law and Shepard’s, and president and CEO of LexisNexis Puerto Rico. Earlier, he was vice president of marketing. He was recognized this year as among the Fastcase 50, honoring the “smartest, most courageous innovators, techies, visionaries, and leaders in the law.”

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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.


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.”

As I reported yesterday, LexisNexis has acquired legal-research start-up Ravel Law. One of Ravel’s most significant projects over the past two years has been its collaboration with Harvard Law School to digitize Harvard’s entire collection of U.S. case law, said to be the most comprehensive and authoritative database of American cases anywhere outside the Library of Congress.

As I reported when the digitization project started, part of the agreement between Ravel and Harvard was that access to these cases would remain free to everyone. Ravel could sell access to advanced tools for case analytics and research, but the basic ability to search and read these cases would be free. LexisNexis said yesterday that it was committed to maintaining that free access.

Today, Harvard released a statement confirming that public access to these cases would continue. The statement quotes Jonathan Zittrain, vice dean for library and information resources:

We embarked on this project knowing that a startup as smart and bold as Ravel Law could be acquired by any number of businesses, including those long involved in commercial legal research. Our agreements were inked with these possibilities in mind, and key benefits and obligations of those agreements will now flow to LexisNexis. We look forward to completing this project according to its long-planned timetable, and to exploring other opportunities with anyone interested in promoting free and open access to primary legal materials, which in turn promotes the cause of justice.

This is as I suspected — there were contractual commitments to keep this information public and LexisNexis will inherit those commitments.

In major legal-industry news, LexisNexis Legal & Professional today announced its acquisition of Ravel Law, the legal research, analytics and visualization platform that empowers users to contextualize and interpret large amounts of legal information to uncover valuable insights.

Rumors of the impending acquisition have been circulating for weeks. This morning, I spoke with Jeff Pfeifer, VP of product management for LexisNexis, and Dan Lewis, CEO of Ravel Law, who provided details of the acquisition.

Notably, the acquisition moves LexisNexis further in a direction it has been heading for a few years now of expanding its suite of legal analytics products. In addition to its own analytics products, LexisNexis MedMal Navigator and LexisNexis Verdict & Settlement Analyzer, LexisNexis last year acquired Intelligize and Lex Machina.

“This acquisition builds on investments we’ve been making to deliver deeper analysis for today’s lawyer,” Pfeifer said. “Our vision is to create the data-driven lawyer of the future. Daniel and I deeply share that same passion and deeply share that interest in driving new insights out of technology that were not previously available.”

Pfeifer said LexisNexis will be fully integrating Ravel Law’s judicial analytics, data visualization technology and unique case law PDF content from the Harvard Law Library into Lexis Litigation Profile Suite and Lexis Advance. Those first integrated offerings should come to market in early 2018, Pfeifer said.

After acquisition, Ravel Law’s analytics offerings will continue to expand and be fully integrated into Lexis Litigation Profile Suite, delivering new insights around judicial behavior that complement the product’s current expert witness intelligence, LexisNexis said.

Additionally, Ravel Law’s case law data visualization tool will be integrated into Lexis Advance, expanding the platform’s current visualization offerings.

“For our part, one of the things I’m most excited about is not to consider this a finish line for Ravel,” said Lewis, “but rather a next step, and through LexisNexis’s global reach to extend our reach to millions more people than we otherwise could.”

Since 2015, Ravel Law and Harvard Law School have been engaged in a joint project to digitize all U.S. case law. All of that case law content and PDF images of original case opinions will become part of the already expansive case law collection available from LexisNexis. Ravel had committed to maintain free and open access to that historical collection, and LexisNexis says it is committed to continuing that access.

“LexisNexis is truly leading the development of the field of Legal Analytics—through our content, tools, and engineering expertise,” said Jeff Pfeifer, vice president of product management at LexisNexis. “With the acquisition of Ravel Law, we’re gaining more than technology and content—we’re also gaining exceptionally talented people. The Ravel Law team has a proven track record of innovation, and we’re excited to have them on board.”

“The Ravel Law team is excited to join LexisNexis for many reasons, chief among them is that we share a vision for the role of technology in the practice of law in which innovative, highly effective and easy to use tools help lawyers make data driven decisions,” said Daniel Lewis, CEO of Ravel Law. “We look forward to bringing our expertise and technology to that effort at LexisNexis.”

Ravel Law and its team will continue to be based in San Francisco. All Ravel Law employees have been offered positions to remain with the company.

I will have more on this later.

The legal research service Ravel Law today announced the launch of a new feature, Firm Analytics, that provides insights on law firms’ litigation histories that can be used for competitive intelligence and research into firms’ litigation activity.

I am traveling today and have not seen this new feature. Ravel CEO Daniel Lewis says it can be used to:

  • Understand a firm’s litigation history by case type, venue, motion win rate, and judge.
  • Rank and compare firms by their case volume and motion win rate across more than 30 practice areas and specific venues.
  • Create custom comparisons and reports using an array of variables.

By way of example, Firm Analytics can be used both by firms and by in-house counsel to gain insights into firms’ experience and performance. It could also be used by an associate working on an employment law case to quickly find the previous employment law cases the association’s firm handled, understand the motions involved and past win rates, and discover the arguments that worked best.

Lewis says that Firm Analytics provides a new Ravel framework for integrating with firms’ internal document management systems, making possible the combination of public and private material for an even more comprehensive and seamless research experience.

Firm Analytics also provides rankings of firms across key variables, including practice area, case volume, venue experience, and motion win rates. These leaderboards allow comparisons of firms across substantive performance metrics.

This is Ravel’s fourth analytics product. Last year, it launched Judge Analytics, Court Analytics, and Motion Analytics.



The legal research service Ravel Law, which last year launched Judge Analytics to provide analysis of how individual federal court judges make decisions, today is launching Court Analytics, a similar feature that applies analytics to an entire court, including all its cases and judges.

(For more on Ravel Law’s Judge Analytics, see my posts here and here.)

With Court Analytics, you can see, for example, a court’s most-cited opinions and judges, as well as the opinions and courts it most frequently cites. It also lets you identify how courts and judges have ruled in the past on particular issues or motion types.

Court Analytics includes the ability to apply filters by motion types, keywords, topics and date ranges. There are a number of predefined filters by topics of law and motion types, but you can also enter any keyword to apply it as a filter.

To use Court Analytics, you begin by selecting a court. Thank’s to Ravel’s digitization partnership with Harvard Law School, its case law collection includes all federal and state courts.  (Go here for a full description of Ravel’s court and date coverage.)


Once you select a court, you come to a page showing its opinions arranged by how many times they’ve been cited. In the 1st U.S. Circuit Court of Appeals, for example, the most-cited case is U.S. v. Zannino, 895 F.2d 1 (1990), which has been cited by 1,476 opinions.

I can move away from this opinions view by selecting a tab labeled Analytics. This gives me three sets of analytics:

  • Opinions, showing the opinions — from whatever court — that the 1st Circuit most frequently cites in its own opinions.
  • Courts, showing the courts that the 1st Circuit most frequently cites. As you might expect, it most frequently cites itself, followed by the Supreme Court, the 9th Circuit and the 5th Circuit.
  • Judges, showing the judges whose opinions are most frequently cited by the 1st Circuit.

A third tab, About, brings up a list of sitting and retired judges from the court. Select any judge to bring up the same types of analytics discussed above — most-frequently cited opinions of that judge and the opinions, courts and judges that judge most frequently cites.

At any point using any of these analytics, you can apply any of the various filters or multiple filters. If you want to see how a judge or a court has ruled on employment law matters, select that filter to show only those cases.

How would an attorney use these analytics? I put that question last week to Daniel Lewis, the co-founder and chief executive officer of Ravel Law. He described two primary use cases:

  • Forum comparison. If an attorney is forum shopping and wants to compare how different jurisdictions have dealt with a particular issue or motion.
  • Argument crafting. If an attorney is arguing a matter to a court, the argument can be made more persuasive by knowing which authorities that court or judge finds most persuasive.

“Attorneys will be able to use it to see how a court has dealt with cases on a particular topic or motion, what they key cases are they should know about, and the particular rules, standards and language that are most important in that venue,” Lewis said.

Although basic access to Ravel Law is free, its Court Analytics and Judge Analytics features are available only to paid subscribers. Ravel does not publish its pricing on its website but requires customers to call for  information on subscription plans.

Later today, Ravel will be hosting a launch webcast to share more details about Court Analytics. The webcast is today (Dec. 5, 2016) at 2 p.m. Eastern time. Register here.

A Massachusetts case from 1884.

An update today on the joint project of Harvard Law School and Ravel Law to digitize Harvard’s entire collection of U.S. case law, which they say is the most comprehensive and authoritative database of American cases anywhere outside the Library of Congress.

Today Ravel posted the complete digitized court opinions of Massachusetts and Delaware, adding to the New York and California cases already posted. This means that, for the first time ever, the full collections of these states’ cases are now available online and available to anyone for free.

Ravel plans to have all the states digitized and online by early in 2017.

“We’re on a quickening march of releasing caselaw,” Ravel CEO Daniel Lewis told me yesterday. “We’re digitizing through the rest of this year and into early 2017. We’re going state by state.”

Ravel has also started digitizing early federal case law from the 1800s and early 1900s and will be posting that online as well, Lewis said.

As Ravel adds new cases, it also incorporates them into other parts of its legal-research platform, including its Judge Analytics feature, which allows subscribers to explore analytics showing how judges make decisions.

Access to the Harvard cases through Ravel is free to anyone. Ravel charges a subscription for access to its advanced features such as analytics.

Harvard and Ravel call their joint project the “Free the Law” initiative. While Harvard is providing the cases, Ravel is providing millions of dollars to support the scanning project.