Document review is defined here 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 or real estate document analysis, and a wide range of other scenarios where the objective is to rapidly analyse and gain insights into legal and contract data using technology.

(The following companies in bold below are listed in alphabetical order here. Companies A to K are listed on the previous 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

Core Product(s): LawGeex

Main Technology : Machine Learning

Key Use Cases : Contract Review automation

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HQ: Tel Aviv

Other Offices: New York

Total Staff (approx.): 50

Year of Founding: 2014

Development Stage : Fully operational

CEO : Noory Bechor

CTO : Ilan Admon

Main external investors, if any:

Aleph VC, Recruit Holdings, Lool Ventures

Target Market : In-House Counsel, General Counsel and Law Departments

Main Legal Jurisdictions in which you currently operate: United States, UK, Europe, Australia and New Zealand

Reference Clients :

Pricing Model(s):

SaaS annual subscription; cost based on number of contracts

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

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

Our platform and infrastructure are ISO/IEC 27001 certified. All data is fully encrypted, both in transit and at rest, ensuring enterprise-grade levels of privacy and security for all our customers.

Company Description :

LawGeex is transforming legal operations. The LawGeex Artificial Intelligence solution helps in-house legal teams automate the review and approval of everyday contracts.

Founded in 2014 by international lawyer Noory Bechor and leading AI expert Ilan Admon, LawGeex enables businesses to remove the contract bottleneck, helping them focus on high value tasks instead of getting lost in paperwork.

LawGeex ensures the simple question ‘Can I sign this?’ doesn’t slow down businesses, while improving accuracy, consistency and efficiency. Suitable for legal teams of any size, LawGeex has customers in over 15 countries, including eBay, Farmers Insurance, Natixis and Lifetime Fitness.

What is your core product’s key selling point?

We help in-house legal teams automate the review and approval of everyday contracts.

Twitter (or other social media): @lawgeex_

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Core Product(s): LegalSifter (the product), ContractSifter Service, and ContractSifter

Main Technology : NLP/ML

Key Use Cases : Document review and negotiation

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HQ: Pittsburgh, PA

Other Offices:

Total Staff (approx.): 45

Year of Founding: 2013

Development Stage : Fully operational. Product launched in July 2017

CEO :  Kevin Miller, CEO

CTO : Lars Mahler, Chief Science Officer and Co-Founder

Main external investors, if any:  Birchmere Ventures

Target Market : General Counsel, Law Firms

Main Legal Jurisdictions in which you currently operate: United States

Reference Clients : TLT, Horty Springer, Estrella

Note – Pricing transitioning from usage pricing to per user pricing

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

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

Company Description :

LegalSifter’s mission is to bring affordable legal services to the world by empowering people with artificial intelligence. We will achieve our mission by working with the legal profession, not against it. Our clients review contracts in a minute or two using artificial intelligence and the advice of their lawyers and leaders. Users start by uploading draft contracts into LegalSifter. Sifters – software trained to read text, look for specific concepts, and learn over time – then review the document and identify important concepts that demand attention or are missing entirely. The Sifters trigger Help Text, in-context advice tailored to the client’s business and negotiation position.

What is your core product’s key selling point?

Contract review in a minute or two using the advice of your lawyers and leaders

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Core Product(s): Data Extraction Platform; Managed Services; ERP/ DMS Integrations

Main Technology : NLP; Deep Learning

Key Use Cases : Data extraction; Document review; On-going doc management, due diligence for transactions

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HQ: Berlin, Germany

Other Offices: London, New York, Dallas, New Delhi

Total Staff (approx.): 100

Year of Founding: 2012

Development Stage : Fully operational

CEO : Abhinav ‘Abe’ Somani

CTO : Florian Kuhlmann

Main external investors, if any:  DAH Beteiligungs GmbH, Anyon Holding GmbH

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Target Market : Corporate Real Estate; Law Firms; Accounting Firms; Consultancies; Banks; Insurance companies; REITs; Asset Management firms; NPL Servicers; Asset Re-creation companies

Main Legal Jurisdictions in which you currently operate: UK; US; Germany; India; Australia; Italy; Poland; France; Spain; Canada; Netherlands

Reference Clients : Linde; Clifford Chance; JLL

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Pricing Model(s):  NA (info arriving soon)

Software Configuration (e.g. cloud; on-site installation):  NA (info arriving soon)

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

The LEVERTON platform runs on LEVERTON servers in ISO 27001 and ISO 9001 certified data centers which guarantee highest security.

Company Description :

LEVERTON provides deep insights from unstructured data found in corporate and legal documents in more than 30 languages. Trusted by over 100 leading companies to create value through structured data with its AI-powered, deep learning, data extraction platform, LEVERTON is located globally, with offices in New York, Dallas, London, New Delhi and Berlin. Better Data. Smarter Decisions.

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Twitter (or other social media):

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Core Product(s): Software and data products, management, data science, and technology consulting services

Main Technology :  We develop products and consult with organizations using technologies including NLP, ML, network science, expert systems, computer vision, deep learning, distributed systems, crowdsourcing, knowledge management, forensics, gamification/incentive management, and visualization.

Key Use Cases :  Our flagship product, ContraxSuite, is a machine learning-powered contract analytics platform powered by our LexNLP natural language toolkit.

HQ: Michigan

Other Offices: Detroit, MI; Chicago, IL; Houston, TX; Boston, MA

Total Staff (approx.): 20

Year of Founding: Founded as Quantitative Legal Solutions in 2013; re-branded to LexPredict in 2014

Development Stage : Fully operational

CEO :  Michael Bommarito

CSO: Daniel Martin Katz

CTO :  Eric Detterman

Main external investors, if any: None

Target Market :  Our target market includes corporate, law firm, and legal service providers, including both legal and technology audiences.

Main Legal Jurisdictions in which you currently operate: North America, South America, UK

Reference Clients : NA

Pricing Model(s): Pricing models for products range from “free” (open source subject to license terms) to paid support, customization, and training based on client requirements.

Software Configuration (e.g. cloud; on-site installation):    We support deployments on-site/on premises, in the cloud, and in hybrid cloud or virtualization solutions.

Security Standards (e.g. ISO Cert, or other): ISO 27001 certification

Company Description : LexPredict is an enterprise consulting and technology firm. We improve process, technology, and the ways people interact with both. We provide traditional consulting services, but in many other cases, we also build data and technology products, or help seed startups to address unmet needs. We #MakeLawBetter.

…

What is your core product’s key selling point?

ContraxSuite and LexNLP allow organizations to build document and contract analytics solutions that they can audit and customize, and know that they have perfect ownership of their data and trained models.

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Twitter: @LexPredict

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Core Product(s): LinkSquares: The AI-Powered Contract Analytics Cloud

Main Technology : NLP/ML

Key Use Cases : Fundraising, Mergers & Acquisitions, Diligence, Quarterly Reporting, Crisis Management, Internal Legal/Finance Projects

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HQ: Boston, MA

Other Offices: NA

Total Staff (approx.): 20

Year of Founding: 2015

Development Stage : fully operational

CEO : Vishal Sunak

CTO : Eric Alexander

Main external investors, if any:

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Target Market : Corporate Legal, Law Firms, Corporate Finance, Legal Operations

Main Legal Jurisdictions in which you currently operate: United States

Reference Clients : Carbonite, CloudHealth Technologies, DraftKings

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Pricing Model(s):  3 tiers of pricing: Basic, Pro & Enterprise based on features and volume

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

Security Standards (e.g. ISO Cert, or other): ISO 27001, SOC 2 Type II (in progress)

Company Description :

LinkSquares is an AI-Powered contract analytics tool for in-house legal and finance teams. Our customers are saving hundreds of hours and thousands of dollars by eliminating manual contract review. Our technology automatically detects and retrieves key contract terms and provides full-text search that lets you search contracts for specific keywords, phrases, and queries.

What is your core product’s key selling point? Know exactly what’s in your contracts without having to read them one at a time with LinkSquares AI-Powered analytics cloud.

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Twitter (or other social media):  @linksquares

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Core Product(s):

–           Luminance Diligence

–           Luminance Property

–           Luminance Corporate

–           Luminance Discovery

Core Technology :

–           Pattern Recognition Algorithms: Luminance understands language by context and content, not just by key-word search, through harnessing proprietary algorithms to identify patterns in the language of every data room it encounters.

–           Advanced Statistical Probability: Bayesian estimation lies at the forefront of Luminance’s approach, ascertaining meaningful relationships within data but also quantifying the uncertainty associated with such inferences.

–           Supervised and Unsupervised Machine Learning: Machine learning algorithms give computers the ability to learn and teach themselves from the data they are given without being explicitly programmed. This means no human input is needed to identify key similarities and differences across large numbers of contracts.

Key Use Cases : M&A Due Diligence, Real Estate, Regulatory Compliance, Insurance

HQ: London, UK.

Other Offices: Cambridge, Chicago and Singapore.

Total Staff (approx.): 70 staff

Year of Founding: 2015

Development Stage : Fully Operational

CEO : Emily Foges

CTO : James Loxam

Main external investors, if any : Invoke Capital, Talis Capital and Slaughter & May invested in a Series A funding round at the end of 2017.

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Target Market : The flexibility of the platform, in terms of its multijurisdictional and multilingual capabilities and competitive-pricing model, allows Luminance to be targeted towards all legal professionals.

Main Legal Jurisdictions in which you currently operate: Multiple.

Reference Clients : With now over 110 clients, Luminance technology has been deployed by top-tier law firms across 35 countries including over 10% of The Global 100 law firms:

Slaughter and May, Bird & Bird, Holland & Knight, Allens, Wong Partnership, Portolano Cavallo

Pricing Model(s): Most clients of Luminance Diligence pay according to a metered amount of data they are working on within the system on a given day. A small number of customers have also chosen to install an on-premises appliance and are charged a monthly fee. This means that Luminance is priced so that firms of every size can benefit from this new generation of AI technology with organizations being charged only for what they use.

Furthermore, to accommodate for the stop-start nature of M&A activity on a transaction, Luminance offers an archiving service, allowing users to store documents and analysis within Luminance for longer periods of time.

Software Configuration (e.g. cloud; on-site installation): Luminance can be delivered in one of two forms, as a fully-serviced environment hosted in the cloud or as a preconfigured appliance plugged into the customer’s data centres and infrastructure. The application and user experience remains the same regardless of which option is chosen.

Security Standards (e.g. ISO Cert, or other): Information uploaded to Luminance is stored securely on the Luminance cloud servers or on-site appliances with all data stored being encrypted at rest and in transit, using 256-bit SSL encryption, ensuring that document content and metadata are protected.

Luminance security, infrastructure and operational practise have been certified by BSI as compliant with ISO27001:2013.

Company Description:

Luminance is the market-leading AI platform for the legal profession. Trained by legal experts, the revolutionary technology is founded on the latest breakthroughs in pattern recognition and machine learning at the University of Cambridge. Luminance reads and ‘thinks’ like a lawyer, but in volumes and speeds that humans will never achieve. Luminance provides an immediate global overview of any body of legal documents, finding significant information and anomalies without any instruction. Whether used for due diligence, compliance, insurance or contract management, Luminance immediately adds value to a legal team with no set-up or customisation required.

What is your core product’s key selling point?

–           Simple Deployment: Luminance delivers value as soon as it is deployed in a firm, without sacrificing intelligence. Less than an hour of basic orientation, led by Luminance, is needed to begin using the platform allowing lawyers to focus on their work rather than setting up or implementing new software.

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Twitter (or other social media): @luminancetech

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Core Product(s): PrivacyPolicyCheck.Ai

Main Technology: Deep Learning, NLP

Key Use Cases: document review: a free, deep learning-based tool for analyzing privacy policies from a GDPR compliance perspective

HQ: Stockholm, Sweden

Other Offices: Oslo, Copenhagen, Silicon Valley

Total Staff (approx.): 80 (inc. law firm)

Year of Founding: 2014

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

CEO (or equiv): Jim Runsten

CTO (or equiv): Magnus Sundqvist

Main external investors, if any: NA

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Target Market: all types of companies; lawyers and non-lawyers

Main Legal Jurisdictions in which you currently operate: 35+ countries and growing

Reference Clients: NA

Pricing Model(s): Free to use

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

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

Company Description:

Synch is different from other law firms when it comes to software development expertise too. Having employed two qualified lawyers who are also software developers, the company built a client-oriented AI tool entirely in-house.

PrivacyPolicyCheck.Ai is a free deep learning-based tool for analysing a privacy policy from a GDPR compliance perspective. The tool was supplied data and trained by Synch’s GDPR experts. Since its launch in end-June 2018, PrivacyPolicyCheck.AI has been used by hundreds of clients in more than 35 countries.

What is your core product’s key selling point?

Free evaluation of a privacy policy to determine which GDPR requirements, mandatory and optional, are addressed and which are not. The AI has been built and trained by lawyers.

Twitter (or other social media): Twitter @synchlaw

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Core Product(s): Relativity, RelativityOne

Main Technology: E-discovery

Key Use Cases: Relativity is a comprehensive, end-to-end platform used across the EDRM model; and is used for supporting additional technology built on top of the platform via the Relativity App Hub

HQ: Chicago

Other Offices: London, Kraków, Hong Kong and Melbourne

Total Staff (approx.): 850+

Year of Founding: 2001

Development Stage: Fully operational

CEO (or equiv): Andrew Sieja

CTO (or equiv): N/A

Main external investors, if any: Raised $125 million from San Francisco-based Iconiq Capital in 2015

Target Market: Corporations, law firms, service providers, governments

Main Legal Jurisdictions in which you currently operate: Our software is used in over 40 countries around the world

Reference Clients: Relativity has over 175,000 users in 40+ countries from organizations including the U.S. Department of Justice, more than 70 Fortune 100 companies, and 198 of the Am Law 200

Pricing Model(s): For pricing inquiries, please contact [email protected] 

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

Relativity is the on-premises version of our software

RelativityOne is our SaaS product, built on the Microsoft Azure cloud

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

Our SaaS product RelativityOne is ISO 27001 and SOC 2, Type II certified. We are also a part of the Cloud Security Alliance, a not-for-profit organization that promotes the use of best practices for providing security assurance within cloud computing.

Company Description:

Relativity is an e-discovery software platform used by corporations, governments, law firms, and service providers around the world for managing high volumes of electronic evidence for litigation, internal corporate investigations, and government regulatory requests.

What is your core product’s key selling point?

We’ve developed powerful technology to help rethink the cumbersome and arduous task of e-discovery, making it more manageable, efficient, and insightful. Relativity brings the entire process together in a single platform, connected to your most important data and supported by the community of experts you need to untangle it all

Twitter (or other social media):

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Core Product(s): Contract Intelligence Platform

Main Technology: NLP/ML

Key Use Cases: contract analysis, both extraction of information and risk assessment

HQ: Munich, Germany.

Other Offices: NA

Total Staff (approx.): 6

Year of Founding: 2017

Development Stage (e.g. Beta, fully operational): Customer projects, Beta product version

CEO (or equiv): Dr. Sven von Alemann

CTO (or equiv): Moritz Biersack

Chief Data Scientist: Dr. Adriaan Schakel

Main external investors, if any: NA

Target Market: General Counsel and law firms

Main Legal Jurisdictions in which you currently operate: Germany

Reference Clients: BMW, SAP, Glade Michel Wirtz, Hella Aglaia

Pricing Model(s): subscription-based dependent upon seats and modules

Software Configuration (e.g. cloud; on-site installation):   cloud, on-prem possible upon request

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

Company Description:

rfrnz GmbH was founded in 2017 and provides automated contract analysis with AI technology. We use Machine Learning and Natural Language Processing algorithms to help lawyers process and analyse their contracts more efficiently. Our system automatically extracts all relevant information from contracts and provides a risk assessment on unusual, missing or risky clauses.

Our target customers are legal departments and law firms, but also procurement or license management functions. We implement our technology at Dax 30 customers already and are releasing a first product version in fall 2018.

What is your core product’s key selling point?

Contract analysis is 50-70% faster and more accurate than with manual work. It is a significant step towards digitization of the legal function and means significant cost savings if legal routine work can be automated.

Twitter (or other social media): @rfrnz_systems

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Core Product(s):

• Seal Software Platform
• Seal Software Analytic Packs
• Seal Software Enterprise Analytics
• DocuSign Platform Extensions – Total Search powered by Seal, Intelligent Insights powered by Seal (these sold by DocuSign)

Main Technology :

• OCR
• NLP
• Text Analytics
• Semantic Analytics
• Machine Learning

Key Use Cases :

• Contract Discovery
• Content Review
• Content Analytics

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HQ: Walnut Creek, USA, EMEA – Headquarters, London, United Kingdom

Other Offices: New York, North Carolina, New Cairo – Egypt, Georgia – Atlanta

Total Staff (approx.):  Over 240

Year of Founding: 2010

Development Stage :  Fully operational

CEO : Ulf Zetterburg

CTO : Kevin Gidney

Main external investors, if any: Toba Capital

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Target Market : Enterprises: large/global

Main Legal Jurisdictions in which you currently operate: US, EMEA

Reference Clients :

‘We have been using the Seal Analytics platform for our customer and supplier contracts for a number of years now,’ said Robert Jackson, EVP & General Counsel, CyrusOne Inc, a real estate investment trust based in Dallas, TX. ‘ Seal’s legally trained ML experts implemented the system and have tailored it to allow the legal department to provide insight to the business on contractual matters, including liabilities, exposures, and revenue opportunities.’

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Pricing Model(s): : Per document, subscription

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

Security Standards (e.g. ISO Cert, or other): SOC 2 Type 1

Company Description :

About Seal Software

Seal Software is the leading provider of content discovery, data extraction and analytics. With Seal’s machine learning and NLP technologies, companies can find contracts of any file type across their networks, quickly understand what risks or opportunities are hidden in their contracts and place them in a centralized repository. Based in the San Francisco Bay Area, Seal empowers enterprises around the world to maximize revenue opportunities, reduce costs, and mitigate risks associated with contractual documents, systems, and processes. For more information, visit Seal Software at seal-software.com.

What is your core product’s key selling point?

The Seal Intelligent Content Analytics (ICA) AI solution gives users access to a broader and deeper set of discovery, analytics, and insight capabilities. That insight empowers users to manage their business’s legal and regulatory exposure, and extract valuable intelligence and data from complex documents such as vendor and customer contracts, financial documents, lease agreements and a plethora of others.

Main contact email:

Twitter (or other social media):

Twitter: @SealSoftware

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Core Product(s): Review, Training Studio, Lexible Author, Lexible Training

Main Technology: NLP/ML

Key Use Cases: Triaging/Prescreening, Document Review, Contract digitisation, Risk Policy Digitisation, Risk assessment, Regulatory Investigation

HQ: London

Other Offices: Cambridge, UK, and Singapore

Total Staff (approx.): 20

Year of Founding: 2015

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

CEO (or equiv): Tim Pullan

CTO (or equiv): Richard Moss

Main external investors, if any: Guy Laurence, Michael Findlay, Duncan Painter, Taylor Vinters, JQ Wang, Hatcher LLP

Target Market: General Counsel & their teams, Compliance, Procurement & Commercial, Sales, Law Firms

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

Reference Clients: Eversheds Ignite

Pricing Model(s): Platform fee with volume top-ups

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

Security Standards (e.g. ISO Cert, or other): SOC1, SOC2, SOC3, SSAE16 / ISAE3402 compliant, ISO27001

Company Description:

ThoughtRiver is a legal-tech company with offices in London, Cambridge & Singapore. ThoughtRiver simplifies contracting through digitisation using its proprietary contract description framework, Lexible.

ThoughtRiver’s technology supports automated contract summarisation, risk assessment and insight extraction capabilities using advanced AI and NLP technology.

The business was founded in early 2015 following 3 years of early conceptual development of Lexible and currently has a team of 20 employees. With experience as a City law firm partner and latterly a senior corporate executive, founder Tim Pullan started the company as a direct result of his first-hand experience of the friction caused by contracting processes. ThoughtRiver worked closely with senior NLP and machine learning experts at Cambridge University to create the proprietary Fathom Contextual Interpretation EngineTM that enables Lexible datapoints to be automatically identified in contracts.

What is your core product’s key selling point?

ThoughtRiver Review addresses a fundamental problem: you don’t know whether you need to read a contract without reading it. The entire initial contract assessment process is automated by leveraging Natural Language Processing (NLP) capabilities and adding a sophisticated digital risk playbook capability based on Lexible datapoints. We do not simply surface relevant clauses but answer detailed questions about contracts to simulate legal assessment.

Review interprets contracts to provide an understanding of risk and opportunity. Risk includes issues such as liability, indemnities etc (i.e. your top ten negotiated issues) but also regulatory issues such as GDPR, Revenue Recognition, Insurance Liability etc. We also work with clients to help them understand commercial opportunities within their contracts e.g. ability to review pricing or transfer assets to third parties.

Twitter (or other social media): ThoughtRiver

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Core Product(s):

• Vaultedge Contract Analysis
• Vaultedge Contract Review

Main Technology :

• Machine Learning, NLP, Legal Knowledge Graph

Key Use Cases :

• Contract Abstraction, targeted at BPO Firms and In-house Legal Counsels
• M&A Due Diligence, targeted at Law Firms
• Contract Review & Negotiation, targeted at In-house Legal Counsels

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HQ: Bangalore, India

Other Offices:

Total Staff (approx.):   25

Year of Founding: 2015

Development Stage : Fully operational

CEO : Murali Tirupati

CTO : Sajeev Aravindan

Main external investors, if any:  Top Investors from India (Deal terms are not public)

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Target Market : BPO Companies, Inhouse Legal Counsels in Enterprises

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

Reference Clients : NA

Pricing Model(s):

• $10 / contract processed
• Monthly plans for high volumes

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

• Cloud (SaaS) as well as On-premise (On-site installation)

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

• ISO27001 Certified
• Vulnerability Assessment done

Company Description :

Vaultedge is a Legal Technology company founded by graduates from Stanford and IIM Ahmedabad. Vaultedge offers software that uses artificial intelligence to automatically review legal contracts, highlight risks and create summaries. Vaultedge is being used by Fortune-500 companies to save up to 80% of Contract Review and Abstraction time.

What is your core product’s key selling point?

• Accurately extract full provisions as well as specific values
• Automatically review contracts to highlight risks and suggest alternate text
• Most user friendly software in the category

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Main contact email: mailto:[email protected]

(Companies A to K are listed on the previous page.)