AI-ENABLED APPLICATIONS

UNLOCKING THE POWER OF ARTIFICIAL INTELLIGENCE

Offering you the full spectrum of AI-enabled applications
tailored to your organisation.

AI-Enabled Applications

BETTER RESULTS THROUGH BETTER AI

With today’s exponential increase in data volumes. You need AI-enabled eDiscovery that stays ahead of big data.

The Lineal suite of AI-enabled applications for various industries leverage the power of Lineal’s AI platform. They are turnkey, easy to use, and fast to implement. No AI expertise required.

Artificial Intelligence Models (AIM)

AIM stands for “Artificial Intelligence Models.” These models are the building blocks of carefully tailored AI engines that iteratively learn matter-to-matter, subject-to-subject, and client-to-client.

Utilising Lineal’s next-generation AI platform, the technology develops a conceptual understanding of data that continuously learns context and sentiment, allowing for deep cognitive analysis. The response is reported back to the fact finders in the form of “story engines.”

These models are commonly being used for litigation, investigations and compliance purposes; however new applications are being realised daily.

CURRENT USES INCLUDE:

Corporations – Corporate litigation and compliance teams are building tailored libraries of models that iteratively learn, constantly developing a greater understanding of the company’s data. This ever-expanding knowledge is then repurposed, allowing the fact-finders to quickly identify the most crucial documents/information upfront, minimising the necessity for expensive document review, and thus dramatically mitigating costs.

Law Firms – Case teams and practice groups are developing model libraries across discipline that continuously learn from the teams’ analysis processes to expedite search/retrieval across matters-repurposing knowledge. Further, teams are marketing their libraries as a competitive advantage over other firms and creating new solutions for audit and compliance that are proactive, as opposed to reactive.

SAVE YOUR TIME – SAVE YOUR MONEY

Whether you’re a litigator, transactional attorney, in-house, or legal ops, AI can enable you to make better, quicker decisions and help generate more value for your clients or organisation.

Book a Demo
Click to View More:
ECA /Data Analysis / Dynamic Entity Modeling
Compliance Auditing
Streamlines Document Review
PII / Sensitive Data Search
AIM by Lineal

The Process

01. Learn

Taking data from a representative selection of past matters, AIM will begin to contextually learn from your data, seeking behavioural patterns, nuisances, and sentiments.

02. Build AI Models

Lineal builds a custom AI engine model from what is gathered/learned from your data.

03. Apply Models to Data

The AI engine is applied to your data, detecting language patterns, communication analysis, heat-mapping, sentiment, etc.

04. Confirm Success

Lineal’s team will confirm what has been learned with what has been gathered in the application.

05. Story Engine Reporting

Reports are exported showing communication analysis, responsive documents, emotional sentiment, heat mapping, and core document identification.

06. Repeat

Modifications to the model will be applied based upon reporting criteria. The process repeats, with learning being codified for future utilisation, and potentially shared across all other models in a library.

Early Case AI Application (ECAi)

Our mission is to deliver advanced technology to our clients and make them very simple and practical to use, so our clients can simply see whether the documents should be reviewed or not.

The Lineal Early Case AI Application enables you to quickly identify potentially responsive data prior to collection by exposing contextual relationships between custodians and content. Through the use of Lineal’s artificial intelligence models take advantage of advanced algorithms pre-defined filters and best practice workflows.

Demo: See ECAi in Action
Click to View More:
Identify Bots
Identify Conversations
Identify Recommended Custodians
Identify Docs Between Two or More People
Identify Email Addresses
Bringing Cutting-Edge AI to Threading
 Reducing the Complexity of Document Review 

Damon Goduto - Partner at Lineal

“Our custom developed LTAi application has reduced the overall document count required for review. Our clients have been getting over 100% suppression on communication threads compared to traditional threading algorithms. This is another example of how Lineal delivers cutting-edge AI tech in easy to use way and implements solutions.” – Damon Goduto – Partner at Lineal

Lineal Threading AI Application (LTAi)

The Lineal Threading AI Application is custom-built at Lineal to improve the productivity and workflow around threading.

LTAi provides a simple field in Relativity to designate the documents that should be reviewed. It also offers three different variations of grouping, from less conservative to more conservative, allowing the review team to alter threading strategies depending on time and cost pressures.

Moreover, it identifies important situations that occur after an incremental load, and it flags thread groups that have new members, so tagging can be propagated or the groups can be re-reviewed, carrying the analysis across incremental loads.

  • Ensure increased review speed
  • Reduce the documents needed for review
  • Increase efficiency in delivering consistent documents for production and review
Demo: See How it Works!

PRIV Finder

Utilize next-generation artificial intelligence to cut your privilege review costs to a minimum while reducing your risk of clawback.

ADVANCED MACHINE LEARNING ALGORITHMS 

Identify possible privileged communications between client and attorney with Lineal Priv Finder. Equipped with the most sophisticated AI technology, Priv Finder will discover, sort, and present all potential attorney/client communication based on our Priv Finder Ai model. Advanced machine learning algorithms are informed by a human-guided questionnaire designed by industry experts to powerfully incorporate people, process and technology.

Book a Demo
Our clients routinely save
40-50% on privilege review.
A Breakdown Of

Our Powerful Workflow

01.

Lawyers are discovered without user input, based on association with legal domains, role of the communicator and Ai Bot Detection (removing law firm marketing emails, etc.)

02.

For more effective review, case teams input which lawyers are aligned and adverse and who are inside counsel.

03.

Privileged scores are published inside Relativity along with the reason for the call.

04.

Bot Detector reduces results that are linked to keyword terms.

05.

Snippets are then presented for fast QC and mass tagging by use of Lineal’s SnipShow.

ChatCraft

Keep chat-platform data within existing review workflows with Lineal ChatCraft.

GATHER CHAT DATA SEAMLESSLY 

The type of data that needs to be supported for document review is constantly changing, and recent global events have influenced this fact through a substantive amount of custodian conversations morphing from email to chat platforms (Teams, Slack, G-Chat, WhatsApp, WeChat, etc.). Collecting, analyzing, reviewing, and producing these conversations have become problematic for lawyers.

Lineal ChatCraft is an end to end solution that doesn’t require the attorneys to change their review workflow. ChatCraft allows for chat data to be seamlessly collected, reviewed, tagged, and produced inside of Relativity, RelativityOne and Reveal review applications. The process was designed for discovery lawyers concerned with driving efficiencies for their corporate clients.

Demo: Maintain the Workflow

The Benefits of ChatCraft:

01. Chat data preserved and collected efficiently allowing for downstream review benefits.
02. Links and attachments in the chat preserved, in-line for review.
03. A toggle option to allow chats to be displayed and reviewed as:
– One entire chat per document
– One day of chat messages per document
– Tagging at an individual message level

04. Completely configurable. You can define single choice or multi-choice fields, no need to redact the non-responsive or privilege chat messages and have the capability to mass-tag chat messages.

EFFICIENT WORKFLOWS

Lineal AI applications can save considerable time throughout the review process. Typically clients will apply numerous iterations of filtering to reduce the scope of data for review, AIM can be applied upfront and allows legal teams quick access to relevant documents and key insights.

Old ApproachNew Approach
  • Old Approach
  • New Approach
Still have questions? Get in touch for a chat no matter where you are

Send us an enquiry:

  • This field is for validation purposes and should be left unchanged.

Your information will only be used to contact you with our response to your enquiry, and is lawfully in accordance with the General Data Protection Regulation (GDPR) act, 2018.
For more information on how your data will be processed, read our Privacy Policy

Let us tell you more about the amazing things we do

Contact Us
en English
X