Document review here is defined as using NLP and machine learning techniques to read documents for the analysis and extraction of unstructured data. Key use cases may be projects such as M&A due diligence, real estate document analysis, and a wide range of scenarios where the objective is to rapidly analyse and gain insights into legal and contract data primarily using technology, rather than human review.

(The following companies in bold below are listed in alphabetical order here. Companies L to Z are listed on the following page.) 

• ANVI Legal
• Appriori
• Ayfie Group
• CasePoint
• ContractPodAi
• Diligen
• eBrevia
• Eigen Technologies
• Elevate (CAEL)
• Heretik
• JuriBlox
• iManage (other applications, see listing)
• Kira Systems
• LawGeex
• Legal Sifter
• Leverton
• LexPredict
• LinkSquares
• Luminance
• PrivacyPolicyCheck
• Relativity
• rfrnz
• Seal Software
• ThoughtRiver
• VaultEdge

ANVI Legal – (GANOT LEX SOLUTIONS PVT LTD)

Core Product(s):   ANVI INSIGHT, ANVI INTELLIGENCE, ANVI ROBOT

Main Technology: Supervised & Unsupervised Machine Learning, Pattern Recognition Algorithms.

Key Use Cases: M&A, Doc Review, Due Diligence, Risk Assessment.

HQ: Hyderabad, India

Other Offices: NA

Total Staff (approx.): 15

Year of Founding:  2017

Development Stage (e.g. Beta, fully operational): Fully Operational

CEO (or equiv):  Anirudh Loya

CTO (or equiv): Anirudh Loya

Main external investors, if any: NA

Target Market: Law Firms, NBFCs & LPOs

Main Legal Jurisdictions in which you currently operate: India, USA, UK, All of Continental Europe

Reference Clients: NA

Pricing Model(s): $100* Per user per month. *Minimum 5 Users.

Software Configuration (e.g. cloud; on-site installation):  Cloud and On-Site Installation

Security Standards (e.g. ISO Cert, or other): Cyber security essentials certified, working towards ISO 27001 certification

Company Description:

Anvi Legal is a pioneering research and analysis platform, implementing next-gen Artificial Intelligence solutions within the legal sector. We improve contract management and advance workflow through the use of machine learning and Natural Language Processing, reducing time and money spent on legal research, discovery and document reviews.

What is your core product’s key selling point?

Extract vital information from current contractual agreements to minimize risks and gain unique insight by focusing on specific keywords and clauses. This collaborative tool can be accessed by multiple users and annotated for essential review processes.

Twitter (or other social media): @AnviLegal

—

Core Product(s): Appriori Contratto

Main Technology: NLP/ML

Key Use Cases: Contract review / Contract Automation / Contract Discovery / Contract Analytics

HQ: São Paulo – Brazil

Other Offices: Belo Horizonte – Brazil

Total Staff (approx.): 7

Year of Founding: 6 months

Development Stage : Beta

CEO : Virginia Ribeiro

COO : Luiza Gazola

CTO : Claudio Escudero

Main external investors, if any:  NA

—

Target Market : Legal Departments

Main Legal Jurisdictions in which you currently operate: Brazil

Reference Clients : Confidential

—

Pricing Model(s) : Licensing

Software Configuration (e.g. cloud; on-site installation):  Cloud

Security Standards (e.g. ISO Cert, or other):  SSL certificate / Oracle Cloud certified

Company Description:

Appriori Contratto aims to provide a fast, accurate and intelligent way to review and to search information about risks and opportunities found in the most common contracts executed by legal departments.

Appriori Contratto delivers to its clients three main functionalities: Automation, Discovery and Analytics.

Contratto Automation provides an integrated data extraction from client’s data bases, automatically extracts contracts by classifying main clauses using AI and NLP in Portuguese language.

With the tagged data set, Contratto Discovery provides a quick and easy way to recognize and extract the most relevant information to lawyers about the risks and the opportunities hidden on those contracts.

Contratto Analytics delivers a summarized view of a large volume of contracts just in one single shot and display all critical metrics through our dashboard.

What is your core product’s key selling point? Efficiency and productivity are the key benefits provided by Appriori Contratto. Towards a paperless world.

—

Twitter (or other social media):

—

Core Products:  ayfie Inspector, ayfie Inspector for Relativity, ayfie Locator, ayfie Predictor and ayfie Supervisor

Main Technology :  NLP, Computational Linguistics, Elevated Machine Learning (supervised & unsupervised), Aided Intelligence

Key Use Cases : Text Analytics and Entity Extractions for Forensics, eDiscovery, ECA, Contract Analytics, GDPR compliance, Knowledge Discovery, Content Insights and Predictive Search.

—

HQ: Oslo, Norway

Other Offices: Munich, New York City, San Francisco, Stockholm, London

Total Staff (approx.): 85

Year of Founding: 2009

Development Stage : Fully operational and revenue generating

CEO : Erik Baklid

CTO : Johannes Stiehler

Main external investors, if any:  NA

—

Target Market : Law Firms, General Counsel, Financial Services, Real Estate, Manufacturing

Main Legal Jurisdictions in which you currently operate: United States, Germany, Norway, Sweden, United Kingdom

Reference Clients : Allianz, BAHR, DNB, Economist, Selmer, Siemens, Skanska

—

Pricing Model(s): Subscription

Software Configuration (e.g. cloud; on-site installation):  On-premise or Cloud

Security Standards (e.g. ISO Cert, or other): n/a

Company Description :

ayfie provides market-leading search and text analytics solutions for legal, finance, healthcare, media and GDPR compliance that are based on more than 30 years of research and experience in linguistics, computational linguistics and computer science. Using this knowledge, ayfie combines best-in-class search technology with an innovative text analytics engine — powered by NLP and machine learning — to deliver efficiency and better insights to businesses in all industries worldwide.

What is your core product’s key selling point?

Ability to extract valuable insights from unstructured data, such as contract parties in agreements, providing increased granularity and more out of the box functionality than machine learning. Document specific extractions can be filtered and queried using ayfie’s smart search solution. Conditional extractions and business rules can be applied to any data extracted.

—

Twitter (or other social media): @ayfie_group

—

Core Product(s):  Casepoint

Main Technology: Artificial Intelligence; Cloud Analytics and Collections; Technology Assisted Review (TAR); Machine Learning

Key Use Cases:

Litigation Management; eDiscovery Review and Production; Data Processing; Early Case Assessment; Case Strategy

—

HQ: Washington, DC, US

Other Offices: Minneapolis, Los Angeles, Dallas; Gujarat, India

Total Staff (approx.): 250

Year of Founding: 2008

Development Stage: Fully operational

CEO (or equiv): Haresh Bhungalia

CTO (or equiv): Vishal Rajpara

Main external investors, if any: None

Target Market: Law Firms, Corporations, Public Sector

Main Legal Jurisdictions in which you currently operate: United States

Reference Clients: Cohen Milstein, Barnes & Thornburg, Briggs and Morgan, Beveridge and Diamond

Pricing Model(s):

Casepoint provides simple, predictable, all-inclusive pricing, including unlimited monthly access to Casepoint’s features for one transparent price per gigabyte. There are no hidden user fees and professional services are provided on a clear time and materials basis.

Software Configuration (e.g. cloud; on-site installation):    Cloud

Security Standards(e.g. ISO Cert, or other):

Company Level

• ISO 27001:2013 Certified
• ISO 9001:2015 Certified
• SOC 2 Type II Accredited
• Strict chain-of-custody
• Regular internal and 3rd-party security audits: penetration testing

Data Center Level

• Biometric & physical ID authentication protocols
• Private security enclosure
• SOC 1 Type II Accredited
• SOC 2 Type II Accredited
• ISO 27001:2013 Certified PCI DSS Certified
• HIPAA Compliant

Web Application & Database Level

• Data encryption at rest and in transit (FIPS 140-2 validated 256-bit AES encryption and TLS 1.2 protocols)
• Role-based security
• Full audit-logging capabilities
• Two factor authentication
• FedRAMP (expected Q1 2019)

Company Description:

Casepoint is a technology company focused on the digital transformation of litigation discovery. Casepoint’s cloud-based eDiscovery platform removes significant barriers from the discovery process, enabling legal teams to focus on the art of litigation.

Features of Casepoint include a full-strength review platform with artificial intelligence pre-installed, cloud analytics and collections, and robust data processing capabilities all in a single technology platform. Based in the United States and with offices in three continents, Casepoint is repeatedly chosen by leading law firms, multinational corporations, and public sector clients for their largest, end-to-end discovery needs. Casepoint is smarter eDiscovery.

What is your core product’s key selling point?

Casepoint offers all the full-featured eDiscovery capabilities similar to other tools on the market, however they offer some very important extras. Casepoint is easier to navigate and takes fewer clicks to get the user where they want to go. Also, Casepoint provides one unified platform, which means once data is ingested, all the discovery phases are supported within a single solution, from Processing, ECA, Analytics and Review to TAR and Production.

However, what truly sets Casepoint apart is the CaseAssist Artificial Intelligence (AI) functionality, which comes pre-installed into Casepoint. This greatly enhances document analysis and review, saving time and money.

—

Twitter (or other social media):

Twitter: @Casepoint

—

Core Product(s):  End to end CLM solution and contract review tool

Main Technology: NLP/ML

Key Use Cases: Contract automation, doc review, repository management, lifecycle management, risk assessment, legal front door, eSignature

—

HQ: London

Other Offices: New York, Glasgow, Mumbai

Total Staff (approx.): 50

Year of Founding: 2014

Development Stage (e.g. Beta, fully operational): Fully operational

CEO (or equiv): Sarvarth Misra

CTO (or equiv): Nanda Vythelingum

Main external investors, if any: NA

—

Target Market: General Counsel and Law Firms

Main Legal Jurisdictions in which you currently operate: All

Reference Clients: NA

Pricing Model(s): Per user per month

Software Configuration: Cloud preferred but also available on premise.

Security Standards (e.g. ISO Cert, or other): All client data is hosted on MS Azure, which beneits from its class security standards.

Company Description:

ContractPodAi is an easy to use, intuitive and affordable contract creation and lifecycle management solution. It allows users to assemble, automate, approve, sign and manage all their contracts and documents.

Now one of the world’s fastest growing contract management systems, ContractPodAi has already digitally transformed the contract management processes of organisations such as EY, Total Petroleum, UEFA, Bosch Siemens and Pennon Group. ContractPodAi also works with some of the UK’s most dynamic law firms, both internally and to enhance their service offering to clients.

ContractPodAi is headquartered in London with a global presence with offices in New York, Glasgow and Mumbai – and clients spanning Europe, America, South East Asia and Australia.

What is your core product’s key selling point?

It’s an end to end system which means the user can do everything from the initial contract request to archiving the signed document.

Twitter (or other social media): @ContractPodAi

—

Core Product(s): Machine learning software for contract review

Main Technology : NLP/Machine Learning

Key Use Cases : Contract review within law firms and legal departments with specialties in M&A due diligence and lease review

—

HQ: Toronto, Canada

Other Offices: N/A

Total Staff (approx.): >20

Year of Founding: 2015

Development Stage : Fully operational

CEO : Konrad Pola

CTO : Dan Hulton

Main external investors, if any:

—

Target Market : Law firms and in-house legal teams

Main Legal Jurisdictions in which you currently operate: Global

Reference Clients : Available on request

Pricing Model(s): Diligen is available as a monthly subscription based on document volume, starting at 50 documents/month for small teams and scaling to over 10,000 documents/month for enterprise clients. For more information please see https://www.diligen.com/pricing/

Software Configuration (e.g. cloud; on-site installation): Cloud, private cloud available

Security Standards (e.g. ISO Cert, or other): Datacenter ISO 270001

Company Description :

Diligen is an AI contract assistant that helps lawyers review contracts in half the time by identifying key provisions automatically, producing contract summaries and helping teams manage the contract review process. Diligen is used by teams all around the world that range from small firms and legal departments to the very largest global firms and corporations.

What is your core product’s key selling point?

Diligen helps lawyers and legal teams review contracts faster and more efficiently. Diligen combines fast, accurate identification of key contract terms with collaborative project management. Our clients tell us that they love Diligen’s ease of use, from the ability to sign up for Diligen online to our intuitive and easy-to-use interface. In addition to the library of clauses that Diligen is pre-trained to recognize, clients can train the system to identify new clauses to customize Diligen for their needs. Diligen is available at a flexible monthly subscription which allows clients to select a plan that suits their requirements – whether they want to review 50 documents a month or 5000.

Twitter (or other social media):  @diligensoftware

—

Core Product(s): eBrevia Contract Analyzer

Main Technology: NLP/ML

Key Use Cases: Document Review, Mergers & Acquisitions, Contract Management, Compliance Projects, Vendor & Customer Management, Real Estate & Other Lease Review, IP Management, Human Resources Document Review.

—

HQ: New York, NY

Other Offices: New York City, London, San Francisco.

Total Staff (approx.): 20

Year of Founding: 2011

Development Stage (e.g. Beta, fully operational): Fully operational

CEO (or equiv): Ned Gannon, Adam Nguyen

CTO (or equiv): Jacob Mundt

Main external investors, if any: NA

Target Market: Audit/Consulting Firms, Law Firms, Corporate Legal Departments, Financial Institutions, Legal Process Outsourcers, and Commercial Real Estate Firms.

Main Legal Jurisdictions in which you currently operate: USA, Europe

Reference Clients: Thomson Reuters, PwC, Baker McKenzie

Pricing Model(s): Based on document upload, not number of users.

Software Configuration (e.g. cloud; on-site installation):  Cloud (multi-tenant or single-tenant) or on-site installation (on-prem).

Security Standards (e.g. ISO Cert, or other): NA

Company Description:

eBrevia uses industry-leading machine learning and natural language processing technology developed in partnership with Columbia University to extract data from contracts, bringing unprecedented accuracy and speed to contract review and analysis. eBrevia’s clients come from a variety of industries, including energy, education, technology, legal, heavy equipment, industrial products, telecommunications, commercial real estate, audit/consulting, business process outsourcing, financial services, professional services, pharmaceutical, and private equity. They include some of the world’s largest corporations, law firms, and audit/consulting firms.

What is your core product’s key selling point?

eBrevia reduces the time spent on tedious contract review while increasing the reviewer’s accuracy. We have the most precise AI on the market, a simple yet feature-packed user interface, and powerful self-training features to easily teach the AI new concepts.

Twitter (or other social media):

Twitter:                      @eBrevia

—

Core Product(s):  NLP extraction, NLP classification, fuzzy matching

Main Technology : NLP driven by machine learning

Key Use Cases : System is flexible enough to handle most use cases involving extraction and classification. Examples: analysis of multiple document types (e.g. contracts, emails, invoices, time entries etc.), regulatory compliance, risk assessment, due diligence, data analytics, data reconciliation, RWA optimisation.

HQ: 36 King Street, London WC2E 8JS, UK

Other Offices: 131 Varick Street, New York, NY 10013

Total Staff (approx.): 60

Year of Founding: 2014

Development Stage : fully operational

CEO : Dr Lewis Z. Liu

CTO : Dr Lewis Z. Liu

Main external investors, if any:  Goldman Sachs PSI and Temasek

Target Market : financial institutions, insurance companies, law firms, large corporates, healthcare providers, and public-sector organisations.

Main Legal Jurisdictions in which you currently operate: UK, USA, EU, Singapore, Hong Kong, and China.

Reference Clients : Goldman Sachs, ING, Linklaters, Evercore

Pricing Model(s): : volume/usage-based.

Software Configuration (e.g. cloud; on-site installation): both cloud and on-site installation available.

Security Standards (e.g. ISO Cert, or other): Cyber security essentials certified, working towards ISO 27001 certification.

Company Description :

Eigen is a research-led artificial intelligence company based in London and New York. Our mission is to help individuals and organizations make the right decisions, and we do this by unlocking the value of their qualitative data.

Eigen automates the extraction and classification of information from documents. Our simple, flexible Natural Language Processing (NLP) technology accurately extracts information from diverse types of documents at scale and can be integrated into our clients’ workflows. We use state-of-the-art machine learning algorithms to recognize patterns in text and give accurate answers to unique questions. This enables our clients to use data in new ways to make the right business decisions: driving down costs, finding opportunities, calculating risks, and meeting regulatory requirements.

Founded in 2014, our clients include some of the most respected names in finance, law, and professional services. As a research-led company, we translate the latest methodologies from applied physics, mathematics and machine learning into the technology that underpins our product.

What is your core product’s key selling point?

Eigen puts you in full control of the machine learning process.

• Low training data requirements
• Total flexibility
• High accuracy
• Simple, iterative training
• APIs for integration with your systems
• Audit trail transparency
• On-premise deployment

Twitter (or other social media):  @Eigen_Tech

—

Core Product(s):  Our product, Cael, is a suite of tools for helping lawyers ‘manage’ and ‘perform’ legal work. That suite of products includes the following apps:

Explained a different way, out suite of apps is designed to support the following legal work framework:

Main Technology:

We deploy and integrate various AI components (mainly NLP/ML) through the suite of applications.  We call it Cael ME2 (Machines and Expertise in Everything).

Each product is at various stages of maturity as it relates to use and integration of AI and machine intelligence into its workflow.  We have outlined below the specific use cases we are training and/or delivering through our machine learning capabilities:

Product	AI Use Cases
Cael DealRoom	–        Auto-extraction of clauses for validation/review –        Auto-development of review forms and checklists based on historical deals and/or set of contracts uploaded –        Auto-identification of “risky” contracts based on analysis of loaded contracts
Cael  Contracts	–        Auto-identification of historical agreements relevant to existing record/request –        Auto-comparison/benchmark of agreement against repository –        Auto-flagging of potential risk on current contract against standard clauses/deviations –        Auto-generation and self-service of request –        Auto-assignment based on triage path –        Auto-extraction of clauses for efficient validation/storage of contract
Cael BillPrep	–        Auto-improving accuracy of rule sets based on user acceptance/overrides of flags –        Auto-indication of invoice health based on pattern recognition –        Downstream, point in time (at the point of time entry) alerts/prompts to users if non-compliance with guidelines is detected –        Automapping of OCG document to rule sets based on auto-analysis of the OCG document
Cael Verify	–        Auto-identification and recommendation of relevant/similar strings of text to verify based on initial selection –        Auto-analysis of historical verification documents for identification of who previously verified which statements (for go-forward assignment efficiency) –        Auto-analysis of document verification bank for identification of previously verified similar statements and location of evidence –        Auto-comparison of newly uploaded document versions
Cael Project	–        Auto construction of matter plans based on pattern recognition –        Intelligent identification of risk based on pattern recognition (i.e. this matter is likely to go over budget based on X, Y and Z historical pattern analysis) –        Auto-mapping of unstructured time records to matter plan phases/tasks –        Intelligent email notification system (learns based on your email interaction which email notifications you like, dislike, etc.) –        Matter Planning advisor – remembers to ask you certain questions at each point of matter plan (based on historical matter analysis;  i.e. if it notices that you are developing a type of matter, but forgot to include a certain task or assumption, it prompts you as a reminder) –        Go forward predictor of timelines and finances based on historical pattern recognition as a measure of how likely the time allocated and estimate will be met.
Cael Vision	–        Auto-identification of data duplicates and merging of similar records (de-duping) –        Auto-identification and transforming of data upon load (merging values, etc.) –        System learns to identify your spending trends to assist in budgets year over year (Budget topics are constantly coming up)
Cael Select	–        Auto-proposal of Panel/ Off Panel Firms based on NLP/ML analysis of outcomes, deliverables & matter types (the lawyer’s actual choices would form the correction/ML mechanism) –        Auto-proposal of matter plan outline & staffing hours based on identified outcomes, deliverables & matter types –        ML auto-scoring of Firm proposals per a) experience of lawyer scoring and b) typical ‘market’ matter planning/pricing; if you can do (2) above, this is the next consequential step

HQ:  Los Angeles, CA, US

Other Offices:

• Silicon Valley (Milpitas), US
• Phoenix, US
• New York, US
• Chicago, US
• Houston, US
• Delhi, India
• Manila, Philippines
• London, UK
• Oxford, UK
• Sydney, AUS

Total Staff (approx.):  550 associates worldwide

Year of Founding:  2011

Development Stage:

Product	Stage
Cael DealRoom	Fully Operational
Cael  Contracts	Beta
Cael BillPrep	Beta
Cael Verify	Beta
Cael Project	Fully Operational
Cael Vision	Fully Operational
Cael Select	Beta
Cael Flow	Beta

CEO (or equiv): Lokendra Tomar, CEO

CTO (or equiv):  Pratik Patel, VP Products

Main external investors, if any: NA

Target Market:  Law Departments and law firms

Main Legal Jurisdictions in which you currently operate:   We are a global company, operating in all regions of the world.

Reference Clients (optional):

Disclosed upon request

Pricing Model(s):  all of our products are sold on an annual subscription basis; Customers can also opt to use Cael Contracts and Cael DealRoom on a project basis if desired.

Software Configuration (e.g. cloud; on-site installation):   All Cael products are cloud-based software solutions.

Security Standards (e.g. ISO Cert, or other):   

• ISO 27001
• External Pen Tests and Audits on a yearly basis
• Encryption at rest (with option to further encrypt with client keys)
• Further, we adopt the security standards of Azure and AWS since our applications are hosted on their cloud servers

Company Description: 

Elevate is a global law company, providing consulting, technology and services to law departments and law firms. The company’s team of lawyers, engineers, consultants and business experts extend and enable the resources and capabilities of customers worldwide. Elevate is the most-used law company according to the 2017 State of the Industry Survey published by the Corporate Legal Operations Consortium (CLOC) and has been ranked as a top global legal services provider by Chambers & Partners for four years in a row. Elevate was also ranked on the Inc. 5000 Fastest Growing Private Companies list for two years in a row, including No. 53 in 2016.

What is your core product’s key selling point? 

Cael’s key selling points are:

• provides lawyer-friendly, cloud-based applications for ‘managing’ and ‘performing’ legal services.
• equipped and designed to augment legal teams with machine intelligence and capabilities

Twitter (or other social media):

@elevateservices

—

Core Product(s): Heretik Relativity Application

Main Technology : Machine Learning & Self-Service ML Pipeline

Key Use Cases : Significant Volume Contract Review Projects:

Due Diligence / Post-Merger Integration

Employment Benefits

Tax Reform & Regulation

Project Forecasting

HQ: 205 West Wacker Suite 516 Chicago, IL United States

Other Offices: San Francisco, CA

Total Staff (approx.): 11

Year of Founding: 2016

Development Stage : Fully Operational and being used on live matters

CEO : Charlie Connor

CTO : Andy Abbott

Main external investors, if any:  Relativity, Corazon Capital, Chicago Ventures, Service Provider Capital

—

Target Market : Law Firms and Professional Services Firms

Main Legal Jurisdictions in which you currently operate:  United States, United Kingdom, and Australia.

Reference Clients : Reed Smith/Gravity Stack

—

Pricing Model(s): Available upon request

Software Configuration (e.g. cloud; on-site installation):   Cloud and on-site installation

Security Standards (e.g. ISO Cert, or other): Available upon request

Company Description :

Heretik is a machine learning solution that removes risks, meets obligations, and realizes opportunities within contracts. Built on top of Relativity, law firms are able to extend their favorite e-Discovery tool to corporate transaction teams; enhancing best practices with minimal disruption.

From inception, we’ve prioritized cutting-edge machine learning technology along with workflow capabilities to allow users to take immediate action on their contract data. Whether managing massive M&A transactions, comparing messy employment agreements, or extracting critical data in bespoke contracts, our machine-learning solution reduces days or weeks of work to minutes. The results? More accurate bids, better win rates, larger capacity to manage contracts, and expanded footprints within key accounts.

What is your core product’s key selling point?

Whether your priority is to accomplish better results faster in your core offerings, or to find new ways to deepen your client relationships – Heretik can help you stay at the cutting edge of what is possible. By seamlessly integrating with Relativity – we enhance your current best practices with minimal disruption or integrations required.

Twitter (or other social media):

Twitter: @heretiksoftware

Instagram: @heretiksoftware

—

Core Product(s):

• Document and Email Management:
  • iManage Work, iManage Share
• iManage RAVN Artificial Intelligence
  • Insight, Classify, Extract
• Security + Information Governance
  • Threat Manager
  • Security Policy Manager
  • Records Manager

Main Technology: Various.

Key Use Cases: Due Diligence, Lease Term Extraction, ISDA MA/CSA, Time Card Narrative

HQ: Chicago, Ill, USA

Other Offices: Silicon Valley (Sunnyvale, CA), London (2 offices), Belfast, Bangalore

Total Staff (approx.): 450

Year of Founding: July 2015 (divestiture from HP); 1998 – initial founding date

Development Stage (e.g. Beta, fully operational): Fully operational and independent

CEO (or equiv): Neil Araujo, CEO

CTO (or equiv): Mohit Mutreja, CTO

Main external investors, if any: N/A

Target Market: Law Firms, Corporate Legal Departments, Financial Service Firms, Account Firms and other professional services firms

Main Legal Jurisdictions in which you currently operate: UK, EU, USA, APAC.

Reference Clients: Case studies on the website.

• Johnson Winter & Slattery
• Keoghs
• Clayton Utz
• Reed Smith

Pricing Model(s):

Annual subscription basis based on user base plus volume usage metric.

Software Configuration (e.g. cloud; on-site installation):    on-prem, Cloud, hybrid Cloud

Security Standards (e.g. ISO Cert, or other):

iManage has a security and compliance program that supports the following regulations, standards and frameworks

• ISO 27001 & ISO 27002 (all controls)
• ISO 27017
• ISO 27018
• ISO 22301
• SOC 2 Type 2
• NIST 800-171
• HIPPA
• DFARS 252.204-7012

Company Description:

iManage transforms how professionals in legal, accounting and financial services get work done by combining the power of artificial intelligence with market leading document and email management. iManage automates routine cognitive tasks, provides powerful insights and streamlines how professionals work, while maintaining the highest level of security and governance over critical client and corporate data. Over one million professionals at over 3,000 organizations in over 65 countries – including more than 2,000 law firms and 500 corporate legal departments – rely on iManage to deliver great client work.

What is your core product’s key selling point?

The iManage RAVN AI platform combines several synergistic technologies:

(1)      iManage Extract’s machine learning data extraction via out of the box self-service functionality, out of the box pre-trained document level classification plus integration;

(2)      iManage Insight’s enterprise search engine and KnowledgeGraph®, which links “know-how” (documents, precedents, templates, external data and internal systems (e.g. billing, intranet and so on) with “know-who” (experts); and

(3)      the iManage document management system, used by 80% of law firms in each major legal market and a growing number of non-law firm users spanning corporations, financial services and public sector clients.

The iManage RAVN platform can be deployed in the cloud, on premises or in combination.  We also offer a bespoke managed services option to create custom integrations between our own products and those of others (e.g. CLMS, CMS, SharePoint, HighQ etc) and / or extend our product functionality with decision logic to expedite the downstream processing of extracted data triage.

Main contact email: Manjul Gupta, Director of Corporate Communications; [email protected]

Twitter (or other social media):

Follow iManage via:

—

Core Product(s):  Kira

Main Technology : Machine Learning Contract Analysis Software

Key Use Cases :

Kira is used for due diligence, contract obligation management, contracting simplification, cost recovery, regulatory compliance, knowledge management, and other use cases where visibility into contract provisions is critical.

HQ: Toronto, Canada

Total Staff (approx.): 100

Year of Founding: 2011

Development Stage : Fully operational

CEO : Noah Waisberg

CTO : Dr. Alexander Hudek

Main external investors, if any: NA

Target Market : Law firms, Corporations and Corporate Legal Departments, Legal Service Providers

Main Legal Jurisdictions in which you currently operate: United States, United Kingdom, Canada, Australia, Other parts of Europe, South America, Asia, and Africa

Reference Clients : Allen & Overy, Ashurst, BKD, Bowmans Law, Davis Polk & Wardwell, Deloitte, DLA Piper, Fasken, Fenwick & West, Freshfields, Integreon, McCann FitzGerald, Moss Adams, Perkins Coie, Weightmans

Pricing Model(s):

Pricing is based on volume of usage and is sold on an annual subscription basis.

Software Configuration (e.g. cloud; on-site installation):

Cloud-based software, however on-premise installation is available as well

Security Standards (e.g. ISO Cert, or other):

Kira Systems is SOC2, Type 2 certified, attesting to the security of Kira and providing customers with assurance about the security, availability, and confidentiality of the systems used to process their data. Two-factor authentication can be configured by client users. We also support integration for Single Sign-On (SSO).

Company Description :

Kira Systems’ technology is the most used and trusted software for contract review and analysis, helping the world’s largest corporations and professional service firms uncover relevant information from unstructured contracts and related documents. Kira is powerful, patented, award-winning software that excels at searching and analyzing contract text and can be deployed for contract metadata extraction, diligence, lease abstraction, regulatory compliance and other projects where visibility into contract provisions is critical. Using Kira Quick Study, anyone can train additional models that can accurately identify virtually any desired clause. To find out more, please visit www.kirasystems.com.

What is your core product’s key selling point?

Kira is by far the contract analysis software system most-heavily-used by professional services firms, and increasingly used directly by corporates as well.

Kira comes with the ability to identify out-of-the-box over 450 common data points in a wide variety of contracts, agreements, and licenses or the Quick Study feature can be utilized to easily customized to identify and extract any new contract information required.

Twitter (or other social media):  @KiraSystems

—

(L to Z follows – see following page.)