Lawyer Intelligence Augmentation System

Table of Contents


44th Street Tech enables lawyers to accelerate case investigation with actionable insights through cutting-edge legal tech and interactive data visualization

About 44th Street Technologies

44th Street Technologies, a technology firm in the U.S, delivers legal, risk and compliance solutions to law firms and legal service providers. By combining narrative intelligence, learning, and natural language capabilities, 44th Street matter analysis software instantly transforms the way matter-related information is interpreted, streamlines the document management process, and helps lawyers in constructing a winning storyline from day one.

Legal teams face a daily challenge to manage, analyze, interpret, and utilize large data sets. Lawyers around the globe are leveraging 44th Street Tech, voted as a top innovative legal technology startup in the competition at ABA TECHSHOW 2021 Startup Alley, for its following capabilities:

Simplifying narrative building through powerful data visualization

Constructing a winning narrative arc relies on the trial lawyer’s ability to present facts and evidence in a way that alters each piece of evidence’s individual significance by merging it into a coherent story that resonates. This arc establishes a matter’s thematic thread that can be carried all the way to the closing argument. 44th Street Tech enables lawyers to go above fact-finding and build a compelling narrative that does more than sequence facts or tell events in a particular order. Platform’s advanced note-taking and event identification features capture an individual lawyer’s unique process and present it in the form of interactive chronologies and visualizations. Thus, enabling lawyers and legal teams to structure the basis for their multifaceted arguments.

Accelerating matter investigation

Manually searching through a large amount of documentation drastically slows down the momentum of case investigation. It is also highly error-prone. 44th Street’s knowledge management platform speeds up the case analysis process by transforming data into interactive visualizations that empower teams to identify hidden data patterns, discover new questions, and deliver actionable insights. Additionally, the platform consolidates all types of documents and acts as a library to retain them in a single place for easy retrieval and collaboration.

Intelligent mapping relationships between matter and documents

Because lawyers and legal teams deal with a lot of paperwork, the manual classification of documents is often resource-intensive and error-prone. Using artificial intelligence and natural language models, 44th Street helps lawyers find the correlation between multiple case attributes by providing simple yet powerful data visualizations and intuitive search capabilities. Thus, help them reduce the time taken to prepare for all litigation phases, increase efficiency, and free up staff.

Impact numbers

In order to build the next-generation software for the legal industry, 44th Street partnered with High Peak Software to develop an integrated note capturing, data visualization case analytics, document management, and e-discovery narrative platform. Lawyers and other legal associates have started leveraging our AI-powered case analysis platform to develop insights into their cases faster, gaining a powerful competitive advantage over their adversaries. As a result:

  • By leveraging compelling data visualizations for narrative building, lawyers and other legal associates can handle 27% of more work than in the past using multiple systems.
  • The learning curve for the functions in 44th Street Tech is over 63% shorter.

What 44th Street has to say about the collaboration

“One of the great things that the High Peak team has done with 44th Street’s system implementation is that the system is structured in such a way that it adapts to the way you work. It’s intuitive, easy-to-use, and takes a broad view of what our end-users do with all the data, turning it into useful information. Our clients now create a better narrative backed with data visuals and facts.”

John Siniawski, Co-founder and CEO, 44th Street Technologies

“During my time as a paralegal at a large law firm, we primarily used in-house software to manage, review, and prioritize documents for discovery productions; although I have experience with other e-discovery softwares available in the market. The in-house software did little more than open the document for review. We were expected to analyze and prioritize the documents based on issues and relevant facts with separate word documents and charts. Such software, and most software, require constant re-review of the same documents depending on the issue. 44th Street case analysis software’s features such as facts, issues, and notes solve this problem perfectly and will likely save hundreds of hours in re-reviewing documents.”

Joey Zawacki, Paralegal

“What I like most about 44th Street is that it makes sense out of all the discovery data on day one.”

Carman Caruso, Carmen D. Caruso Law

Why did 44th Street Tech first approach High Peak to build a powerful knowledge and intelligence augmentation system?

Dissatisfied with the state of knowledge management processes prevailing in the market and the cost associated with it—especially for businesses that are documentation heavy in nature—44th Street Technologies’s goal was to build a comprehensive platform for better document collection, processing, review, analysis, and visualization from the ground up for the legal industry. 

To solve this issue, 44th Street Technologies connected with High Peak Software to develop an analysis platform that empowers legal entities and lawyers to create powerful narratives and enhance the storytelling experiences with supporting data.

Every litigation matter has thousands of documents such as emails, transcripts, briefs, contracts, and NDAs. Lawyers and legal professionals have to deal with large volumes of paperwork and documentation. Vetting and culling these documents takes multiple reviews which are often time-consuming and costly. These activities include conducting extensive research, creating a chronology and timeline, fact-checking, documentation and review, and much more. A documentation backlog is created if the process to complete these tasks is not automated, smooth, and quick in returning actionable insights. 

In order to enable lawyers from small and medium law firms with a technology advantage, 44th Street Technologies wanted to create a self-learning software to help legal teams:

  • Speed up the case investigation and analysis processes by transforming data into intuitive visualizations that empower lawyers to identify hidden patterns, discover new questions, and deliver actionable insights from day one.
  • Quickly understand the cases, capture their thoughts and notes while enhancing their focus to develop a compelling narrative for clients. 
  • Manage a single source for all their matter-related documentation. Whether those are self-notes, documents from clients and oppositions, facts from any other related matter, or opinions from an external expert, every document is retrievable from one place on the device of their choice.
  • Access and highlight case-relevant information by obtaining accurate reports with custom-tailored interactive visualizations.
  • Easily handle more cases with less overhead by streamlining the document review and analysis process.
  • Retain institutional knowledge regardless of turnover or unforeseen disruptions. The platform acts as a library to retain all types of documentation in a single place for easy retrieval and collaboration.

High Peak encountered and solved for several technical and business challenges during product design and development

Designing a narrative building automated e-discovery platform

The concept of storytelling, or narrative, is integral to any trial lawyer’s preparation. Building a narrative relies on the trial lawyer’s ability to present facts, issues, and evidence in a way that alters each piece of evidence’s individual significance by merging it into a coherent story that resonates. Our team needed to develop an end-to-end solution for lawyers and legal teams that goes beyond a mere e-discovery application to assist them with their trial preparation by constructing a compelling storyline. 

Manual documentation process and information overload

A typical case would mean collecting thousands of documents consisting of scanned PDF files, native documents and emails, images, chat logs, and other related documentation. Relying on manual classification or overtly technical systems for such tasks is complex, resource-intensive, error-prone, and highly inefficient.

Solving for an intuitive, scalable and robust solution with a prime focus on data security

Lawyers and law firms are constantly entrusted with highly sensitive information about their clients. As a course of their business, the need for effective data security is of critical importance. While solving the bottlenecks in the enhanced document analysis process, 44th Street Technologies wanted to ensure that the digital solution they were building would be sophisticated yet easy to use while securely handling highly sensitive matter-related documents. At the same time, the solution should be built for scale and has to be robust enough, as vast volumes of data would be uploaded, processed, and extracted for analysis by the users. 

Complicated user interface

Within legal technology, we noticed that the tech development focus is entirely on the solution’s features, and user experience is not considered necessary compared to a checklist of capabilities. Moreover, based on our primary market research, we recognized a clear need for an intuitive e-discovery platform in the market as e-discovery platforms with a non-intuitive user interface make it extremely challenging for non-technical users to adopt the application and its powerful features to its full potential.

A major challenge for our team at High Peak was to make sure that the application’s user experience and interface design was intuitive and easy to use, making it straightforward for lawyers to navigate and utilize the application swiftly.

Disconnected and unorganized offline workflows

Due to the multiple sources of matter-related information, offline workflows make it very difficult for the entire legal team to collaborate effectively. Information is unorganized and often present in silos, making the discovery process highly counterproductive. Therefore, it was critical for our team to make an integrated system that can act as a single source of truth and help end-users seamlessly adopt new digital workflows. 

Based on the challenges faced by 44th Street Technologies’ team and aligning with the vision to make lawyer’s day-to-day processes more efficient, our partners at High Peak came up with an intelligence augmentation system to cut through the drawn-out process of document review and return end-users emphasis where it belongs – on winning the case.

Product discovery & ideation

At the very beginning, our team of engineers, data scientists, and project managers conducted various brainstorming sessions to understand and define the problem statement that our partner was trying to solve. After gathering the initial set of requirements from all the stakeholders at 44th Street and conducting an exhaustive competitive analysis, our team came up with:

  • An e-discovery platform that quickly identifies connections between documents, initiates review (TAR) and helps lawyers deliver valuable insights faster, and
  • A knowledge management solution that streamlines the matter analysis process and transforms the way legal teams interpret their data.

After the initial product rollouts (beta), we started conducting user interviews to understand how efficiently these solutions are helping our target audience. Consulting with subject matter experts made us quickly realize that the end-users are not comfortable using multiple and separate tools for their daily workflows. We also had to address the ease of user adoption, as our end-users would be moving from their traditional workflows to an integrated digital platform. Our research and focus groups suggested that combining our case analysis tool with an e-discovery platform, and ensuring its optimum user adoption would be the key to our success. 

Product strategy

We started again by rolling out case analytics features—particularly visualizations and search—to help lawyers with their analysis process while ensuring that the functions were correctly targeted. Furthermore, building an intuitive and easy-to-navigate interface was of utmost importance to increase product usability. To solve this, our team started building mock screens before rolling out any new feature. These mock screens are then shared with all the stakeholders, including end-users, for their feedback. The entire application’s interface is designed like that. Slowly and steadily, we started incorporating other appropriate functions into the platform based on industry-specific use cases.

Product-market fit

Our team at High Peak strongly believes that any product has to evolve constantly in order to get categorized as a product-market fit. Our AI-powered system is continuously getting trained/retrained on a vast amount of data that is uploaded on our system. Additionally, our team keeps optimizing existing features and building new ones based on the vision of an all-inclusive platform. 

We also conducted focus groups to ensure we were set out in the right direction. We got our first win when a lawyer used the ‘Timeline’ and ‘Sentiment Analysis’ feature on our platform for the first time and got back to us by saying, “Not only do I know what somebody said, but now I also know how and when they said it in just a matter of minutes. This feature is going to change how lawyers traditionally function.” 

Product architecture

Our designed solution is built on the microservice-based architecture to ensure the platform is scalable, programming language & technology agnostic, provides better security & compliance, and can quickly process large data sets. One of the major highlights for our development team is that the current system is still running seamlessly on the initial architecture. 

Product design

To ensure smooth product adoption and a user-friendly experience, we designed our product interface in such a way that it is highly intuitive and easy to use. Using artificial intelligence and natural language processing capabilities, the product continuously learns and evolves based on the lawyers’ input and adapts according to their workflows. Additionally, lawyers can create general notes and link them back to any matter in the system as required. Thus, capturing their thought process and building a compelling narrative using simple yet powerful interactive data visualizations. 

These are some of the reasons why 44th Street Tech is voted as a top innovative legal technology startup in the competition at ABA TECHSHOW 2021 Startup Alley.

Product development challenges

Building a novel product from scratch comes with its own set of challenges. They are as follows: 

  • Multiple iterations and approaches have to be considered while building every model, which is a resource-intensive process.
  • From a business standpoint, initially, the product usage wasn’t happening in a way that we’d expected.
  • Additionally, to help our client with the best ROI possible, we have a lean team in place working on all the aspects of the product, from product ideation to server cost optimization. 

Product success

The product strategy evolved multiple times throughout its development, but our team at High Peak ensured that product development takes place keeping the end-users’ pain points in the center. As a result:

  • With an almost negligible marketing budget, our product has successfully onboarded multiple clients who are using it daily for e-discovery, narrative building and case analysis needs. 
  • Consequently, the product usage has significantly increased compared to when we first started.
  • More and more potential customers have started talking about it, and our team is super excited to take it to the next level.
  • Our team is currently building new features based on documentation specific extractions to provide specific outputs.
  • The platform is expandable to work in any domain and is currently getting tested in new open markets such as Hedge Fund.

“I have not encountered any other platform available in the market that allows users to identify relevant facts and issues with as much clarity as enabled by the 44th Streets case analysis platform. Moreover, the platform also maintains those categories for easy review in the future. The facts and notes features allow you to go beyond a simple one or two-word tag (which it also offers) when analyzing a document production. Facts and issues allow for a brief analysis of the document, where each relevant issue and fact can be identified, distinguished, and saved individually in the first review.

Most importantly, those facts and notes are easily accessed on the software and direct the user back to the subject document – so there is no need to search through the entire production again. Additionally, the facts, notes, and issues identified during the initial review are automatically composed into a chronology timeline, which provides a valuable starting point for building a narrative. For large document productions, these features are just invaluable.”

Joey Zawacki, Paralegal

The Matter Intelligence Augmentation System comprises several intuitive and insightful functionalities to aid users in building winning narratives

We designed and developed a smart and interactive matter management system to improve knowledge-driven work as well as to improve users’ general processes to optimize outcomes. As any matter involves multiple stakeholders, it operates on role-based access, and caters to four types of users corresponding to their functionality: 

  • Global admin
  • Firm admin
  • Case owner
  • Team member

Once logged in, users can create matters with attributes such as matter titles, dates, facts, notes, etc., and also invite collaborating users to participate in, contribute to, and access details and documents of a particular matter as per their requirement. Moreover, the applications record all the activities that a team member on the case has carried out. This makes collaboration between dynamic teams much easier.

A screenshot of the matter management system depicting the different features of the software
Sample | Overview of the Matter

Automated document classification powered by self-learning algorithms saving thousands of manual hours

Document classification tasks can be a massive bottleneck as they receive a large number of multiple document types to process. Before actually extracting data from these documents and organizing it afterwards, they need to classify these documents into respective categories.

Once a matter is created, our system allows users to upload all kinds of documents such as text, PDF, images, chat logs, etc., in bulk. Our system is powered by intelligent techniques such as Machine Learning and Deep Learning to effectively manage these documents with large amounts of unstructured information. These Machine Learning and Deep Learning models get better with time and help us make the document classification process much faster, more scalable, accurate, and cost-effective when compared with manual classification. 

A screenshot of the automated document classification feature that categorizes content based on file type
Sample | Document Classification

As users start uploading documents, it automatically detects various types of documents and categorizes them based on their formats. For instance, the user can upload contract documents, invoices, images to the platform, and the platform is capable of identifying it as such automatically. Users can then access the files based on their format, folder structure, and type.

Accurate data extraction at scale using intelligent OCR techniques improving processing time

In most situations, documents are available in PDFs, native or image form. Typically, data noise and quality elements pose a challenge to information extraction and data transformation from such documents. These include pen scribbles; watermarks; wrinkled, torn, discolored, smudged, stamps imprinted on the text, randomly occurring black and white grains, dark backgrounds, faded ink, printed with low-contrast or colored ink, and poor dpi of the scan. Furthermore, deriving inference from multiple related sentences in a clause or section is another challenge when processing matter-related documents.

We built an automated data extraction capability using Optical Character Recognition (OCR) technology to solve these specific data extraction problems. It involves AI models that are trained using a large amount of training data for handwritten text images and annotated actual text values. 

Using the OCR engine, printed or written text from an uploaded document or image file is converted into a machine-readable format. Accordingly, this extracted data is categorized by our deep learning algorithms and later used for data processing like editing or searching. For example, the algorithms can understand the extracted information presented in a DD/MM/YYYY format as a date.

Intelligent auto-summarization of emails creating short, easily digestible snippets of important information using NLP

Before going deep into any case, right from the first document itself, sometimes users want to take an overview or get to know a specific case attribute. To solve this use case, our team at High Peak came up with auto summarization of emails functionality.

Using Machine Learning and Natural Language Processing algorithms, our designed system analyzes the text in the documents and displays the summarized text in the form of snippets. A user can use the auto summarization feature to view a summarized version of all the emails in a thread—saving them a lot of time and effort. Additionally, information such as email threads and the number of emails can be viewed by the users working on the case.

Semantic topic clustering to simplify natural search and understanding of case narration

Once the uploaded documents are classified and the data has been extracted, our system starts processing this data. It identifies areas where information is contextually or semantically similar and groups them into clusters. Even though a matter may have hundreds of documents talking about many different topics, clustering directs users to a high-level grouping of relevant data. From the first moment itself, users can see what subjects are covered, as well as in-depth subtopics within those general subject areas as dominant keywords and metadata are put front and center.

A screenshot of the topic clustering feature that groups topics based on certain keywords
Sample | Topic Clustering 

Powerful sentiment analysis using NLP to help understand and dissect the underlying emotions and tonality of proof matter

Keeping in mind our client’s nature of work, our system can also identify the emotional tone about a legal matter within the context of a legal milieu. It can identify and quantify text data, emotional states and subjective information of the topics, persons and entities within it. Thus, helping users understand the context behind a conversation at a glance.

Built using pre-trained natural language processing models, sentiment analysis gauges the sentiment of text as positive, neutral, or negative in the email bodies. These language models learn to predict the sentiment of the text based on the context of the sentence. Each sentence within the email body is tagged as positive or negative. Moreover, our system lets users annotate these tags based on their expertise if required. 

A screenshot of the sentimental analysis feature that highlights text based on the emotion it pick up: positive, negative or neutral
Sample | Sentiment Analysis

Robust knowledge management system to store and protect all relevant and sensitive data under one roof

A well-functioning organization usually requires a well-functioning knowledge management system (KMS). With hundreds of documents associated with a single matter, our system provides effective content management, enabling users to organize all matter-related information and index it as clearly as they want.

The KMS comprises six main categories:

  • Facts: Any insights or conclusions derived from the matter-related documents can be stored as a fact.
  • Notes: The notes feature allows users to maintain reference notes, matter highlights, and any information that is significant to the matter.
  • Issues: High-level and incident-level issues pertinent to the matter can be logged in this section of the KMS.
  • Source: Users can organize and store all the matter-related documents with the source feature. For instance, the number of processed files, unprocessed files, email threads, and so on. This feature enables users to have quick and immediate access to all necessary files in one place.
  • Screenshot: While going through the processed documents, email threads, data visualizations, users may take screenshots for future reference. These screenshots get stored and are available as and when required.
  • Address Consolidation: While mining the text from the documents using the OCR engine, sometimes some characters get misconstrued. To fill the gap of technology limitation, the system lets users correct any mistake while extracting email addresses from the documents. Users can merge/unmerge any duplicate email addresses based on their requirements.

Dynamic visual narratives for actionable insights through timelines, heat maps, relationship analysis, etc.

Our intelligence augmentation system processes and stores client documents, emails, and matter-related files in various visual formats such as timelines, heat maps, and circos charts. These visualizations enable users to explore, manipulate, and interact with matter-related information employing dynamic charts, changing colors, and shapes based on queries or interactions. Importantly, interactive visualizations also offer better access to real-time data, making them valuable in dashboards for teams of different sizes. The ability to view data as it comes in and shifts is vital for users in making the best and most accurate decisions.

Following are the type of data visualization our system offers: 

  • Timelines: As the documents are uploaded, the system notes their time and date and then rearranges all the documents under a matter in a timeline. Users can zero in on critical moments by visualizing all communication patterns at once and identifying trends and important dates with clear graphics that lay the framework for developing an argument.
  • Heat maps of words: Our system enables users with heatmaps to view events (emails and documents) pertinent to any given date concerning a particular case in a timeline format. 
  • Email mapping: Using circos charts, our designed system enables users to access email exchanges between the two parties. This interactive chart also allows them to filter email exchanges by subject, timeline, sender, recipient, and so on.
  • Email thread analysis: Our system processes all the emails that are being uploaded and builds a correlation between all the entities that are involved, such as email, name, domain, date, etc. It helps users filter out documents based on their needs and reduces the time and complexity of reviewing emails by gathering all forwards, replies, and reply-all messages together. 
  • Chronology: While “timelines” showcase a user with all the documents in their raw form based on the dates they were uploaded against an actual timeline, chronology helps users with processed documents in the form of events and snippets. Users can also export this information based on their requirements. 
  • Narrative: To powerfully tell a story, users need to present documents or sets of linked documents in their own preferred sequences. Since chronology and timelines sort documents based on their dates, narrative enables users to rearrange documents such as facts, snippets, events, and notes based on their specific storytelling requirements.
A screenshot of the timeline features that groups the files and create an event timeline of the case
Sample image from the product

Intelligent search mechanism emulating natural language search with Boolean search as an add-on

Our system includes an intelligent search mechanism with local and global search features. Built on elasticsearch, it allows users to search and analyze hundreds of documents quickly and in near real-time. The users are provided with numerous search fields, including exact, proximity, domain, facts, notes, issues, tags, file extension, entities, file metadata, and others. The system also lets users leverage Boolean operators(AND, OR & NOT) to construct the boolean search. Moreover, the advanced search mechanism also comes with the capabilities of highlighting the synonyms of input search terms and terms related to input search terms.

In addition, the user can also search for specific elements on a given tab/page using the local search feature.

A screenshot of the search feature that helps you search for relevant text based on specific keywords
Sample image from the product

“The highlight of the solution would definitely be its ability to analyze relationships & ties within matter-related documents and provide users with its interactive visualizations. Consequently, giving end-users the flexibility to transform their notes into a story while doing any research or analysis.”

John Siniawski, Co-founder and CEO at 44th Street Technologies

Want to see High Peak’s team in action? Let’s talk!

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