General Terms of Service – Enterprise

These terms of service (“Terms“) govern your use of our platform (as defined below). By using Our platform, You agree to be bound by these Terms.

We reserve the right to update these Terms which shall come into effect only 30 days from the date the notice was posted. These Terms were last updated on May 5, 2016. It is effective between You and Us as of the date of You accepting these Terms.

WHAT WE DO

Proov is a SaaS platform (the “Platform“) that streamlines the pilot process by facilitating proof of concept demonstrations (each a “POC“) between those start-ups which sign up for the Platform (“POC Partners“)
and enterprises looking to gain greater access to proven technology. The Platform facilitates the open communication and discovery process which allows both the POC Partners seeking opportunities and the enterprises seeking solutions and innovations
to cooperate, coordinate and enter into mutually beneficial agreements. Simply put, We put You in direct communication with POC Partners so that You can cooperate and find successful solutions.

WHAT YOU CAN DO

We are looking forward to helping You connect with POC’s on our Platform. Therefore, We grant You a non-exclusive, revocable, non-sublicensable, non-transferable worldwide and limited right and license to access and use the Services solely for the purpose
of conducting POCs with POC Partners, provided You fully comply with all of the terms herein (“License“).

WHAT WE NEED FROM YOU

We want to provide you with a great experience. Therefore, You must create a user account, as further detailed in the Additional Terms as may be provided to you by the startup and (i) provide Us with continuous access to one or more of your testing
environments as established on Our cloud server, (ii) maintain your testing environments as established on Our cloud server online and operational while using the Services, (iii) be responsible for the accuracy, quality and legality of Your Data, (iv)
use commercially reasonable efforts to prevent unauthorized access to or use of Your Testing Environment or the Service, and notify Us promptly of any such unauthorized access or use, (v) use commercially reasonable efforts to maintain the Testing
Environments free and protected from Malicious Code; and (iv) perform at least one POC during any six month period so long as you are signed up for the Services. Furthermore, You authorize Us to host, copy, transmit, display and adapt Your Data, solely
as necessary for Us to provide the Services in accordance with these Terms.

OUR COMMITMENTS

Here are some commitments we make to You, We warrant that (i) the Services shall substantially comply with the documentation, (ii) We will use commercially reasonable efforts to maintain the Service in accordance with industry standards, and (iii) We
will not knowingly transmit Malicious Code to You. Additional commitments and responsibilities are available in the Additional Terms document. For any breach of a warranty above, Your exclusive remedy shall be to cease using the Services and to the
extent any ongoing POC is in progress for which you have purchase KPI Suites, as defined below, the refund of the payment for such KPI Suites.

CONFIDENTIALITY

During the term of the POC, You may have access to certain non-public proprietary, confidential and/or trade secret information or data of the POC Partners, regardless of the manner in which it is furnished, which given the totality of the circumstances,
a reasonable person or entity should have reason to believe is proprietary, confidential, or competitively sensitive (together, the “Confidential Information“). Confidential Information shall exclude any information that (i) is now
or subsequently becomes generally available in the public domain through no fault or breach on your part; (ii) You can demonstrate in your records to have had rightfully in your possession prior to disclosure of the Confidential Information by the
POC Partner; (iii) You rightfully obtained from a third party who has the right to transfer or disclose it, without default or breach of these Terms; (iv) You can demonstrate in your records to have independently developed, without breach of these
Terms and/or any use of or reference to the Confidential Information. You agree: (a) not to disclose the Confidential Information you may obtain to any third parties other than to your directors, officers, employees, advisors or consultants (collectively,
the “Representatives“) on a strict “need to know” basis only; (b) not to use or reproduce any of the POC Partner’s Confidential Information for any purposes except to carry out your rights and responsibilities under these Terms; (c)
to keep the Confidential Information confidential using at least the same degree of care You use to protect your own confidential information, which shall in any event be no less than a reasonable degree of care. Notwithstanding the foregoing, if You
are required by legal process or any applicable law, rule or regulation, to disclose any of Confidential Information, you may do so to the minimum extent required to meet your legal obligation.

Your obligations with respect to Confidential Information shall remain in effect until any of the exceptions in Section 6.1 apply. It is hereby agreed and clarified that your undertakings pursuant to this paragraph are for the sole benefit of the POC
Partner, and that We shall have no liability whatsoever with respect to any breach of such undertakings by You. We strongly encourage POC Partners and users to execute a separate NDA in the additional terms if they so choose.

DISCLAIMER

EXCEPT AS EXPRESSLY PROVIDED HEREIN, WE PROVIDE THE SERVICES AND THE PLATFORM TO YOU “AS IS” AND NEITHER PARTY MAKES ANY WARRANTIES OF ANY KIND, WHETHER EXPRESS, IMPLIED, STATUTORY OR OTHERWISE. EXCEPT AS EXPRESSLY PROVIDED HEREIN, EACH PARTY SPECIFICALLY
DISCLAIMS ALL IMPLIED WARRANTIES, INCLUDING ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR ANY WARRANTIES REGARDING THE SECURITY, RELIABILITY, TIMELINESS, AND PERFORMANCE OF OUR SERVICES TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE
LAW. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN, WE DOES NOT WARRANT THAT THE SERVICES WILL BE PROVIDED UNINTERRUPTED OR ERROR-FREE OR THAT IT SHALL MEET YOUR REQUIREMENTS.

YOUR COMMITMENTS

Here are some commitments You make to Us, You warrant that You (i) have the required corporate and legal authority to bind your company or such other legal entity which you represent to these terms; (ii) will not use the Services in connection with
any illegal or fraudulent business activities; and (iii) will not knowingly transmit Malicious Code to Us or to any POC Partner.

FEES AND PAYMENT

Maintaining an account and facilitating POC through the Platform is made available to You free of charge, however we do charge certain fees for additional premium services, including but not limited to Key Performance Indicators services (“KPI Suites“)
and certain predictive analyses, in accordance with the terms set forth on the Site and the Additional Terms as may be provided to you by the startup. To the extent you use a Service plan that is made available for a fee, you will be required to select
a payment plan and provide Us accurate information regarding your credit card or other payment instrument. You will promptly update your account information with any changes in your payment information. You agree to pay Us in accordance with the terms
set forth on the Site and this terms, and you authorize Us to bill your payment instrument in advance on a periodic basis in accordance with such terms.

LIMITATION OF LIABILITY

NEITHER PARTY SHALL HAVE ANY LIABILITY FOR ANY INDIRECT, SPECIAL, INCIDENTAL, CONSEQUENTIAL DAMAGES, LOST PROFITS, LOST BUSINESS OPPORTUNITIES OR LOST DATA WITH RESPECT TO THIS AGREEMENT, PLATFORM OR THE SERVICES, WHETHER OR NOT EITHER PARTY HAS BEEN
ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. EXCEPT WITH RESPECT TO YOUR INDEMNIFICATION OBLIGATIONS, GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, THE MAXIMUM AGGREGATE LIABILITY OF EITHER PARTY IN CONNECTION WITH THIS AGREEMENT SHALL NOT EXCEED US $500.

TRADEMARKS

You permit us to use your name and trademark for presenting You on Our website, among other things, in order for Us to provide the Services. You also permit us to use your name and trademark in order to inform that You have joined the Services. Such
notice may be provided using Our social media outlets.

GOVERNING LAW

These Terms shall be governed and construed in accordance with the laws of the State of Delaware and disputes shall be submitted exclusively to the courts of Delaware.

ADDITIONAL SERVICES

If you do not currently maintain your own testing environment, we urge You to review the additional services We offer which include certain software and hardware products (“Our Testing Environment“).

ADDITIONAL TERMS

Because We provide You with a wide range of services, we may ask You to review and accept Additional Terms as may be provided to you by the startup. Any term not defined shall have the meaning set forth in the Additional Terms. To the extent those Additional
Terms conflict with those contained herein, the terms herein shall govern to the extent of the conflict.

Datasets License

Various datasets are included in the Proov service provided to you (“Dataset(s)”). Such Datasets are licensed under the terms of applicable datasets licenses. Each of the Datasets has its own copyright and its own applicable license conditions.
For details on how you may obtain the Dataset for no charge and for the applicable license terms for each such Dataset, please visit the web-links provided herein and review the license terms of each Dataset detailed below.

  1. Proov – List of Datasets Licenses
    1. NYC Property Tax Bills – http://taxbills.nyc/

    2. Parking Data Stream – http://iot.ee.surrey.ac.uk:8080/datasets.html#parking

    3. Pollution Aarhus Aug – Oct 2014 – http://www.cis.fordham.edu/wisdm/

    4. San Francisco Wind Monitoring – https://data.sfgov.org/Energy-and-Environment/San-Francisco-Wind-Monitoring-Data-Current/bkgs-xaqe

    5. Default Of Credit Card Clients – https://archive.ics.uci.edu/ml/machine-learning-databases/00350/

    6. Gross Income – http://taxbills.nyc/

    7. Chicago City Employees – https://data.cityofchicago.org/Administration-Finance/Current-Employee-Names-Salaries-and-Position-Title/xzkq-xp2w

    8. Household Power Consumption – http://archive.ics.uci.edu/ml

    9. running_app – http://studentlife.cs.dartmouth.edu/dataset.html#sec:sensing:activity

    10. sms – no source was provided.

    11. Gps – http://studentlife.cs.dartmouth.edu/dataset.html

    12. geelong_wi-fi_usage – https://data.gov.au/dataset/geelong-wi-fi-usage/resource/1b25fcaf-7080-4801-98f3-ce441fb810c2

    13. graylog-searchresult – Proov inner dataset

    14. wifi – http://studentlife.cs.dartmouth.edu/dataset.html#sec:sensing:activity

    15. Bluetooth – http://studentlife.cs.dartmouth.edu/dataset.htmlhttp://studentlife.cs.dartmouth.edu/dataset.html#sec:sensing:activity

    16. call_log – http://studentlife.cs.dartmouth.edu/dataset.html

    17. us_coubty_level_use_2010 – http://water.usgs.gov/watuse/data/2010/index.html

    18. us_county_level_use_2005 – http://water.usgs.gov/watuse/data/2005/index.html

    19. Wireless Sensor Data Mining – http://www.cis.fordham.edu/wisdm/

  2. Human Activities Sensor Rich Environment

    Reference is made to any one of the following:

    [1] Daniel Roggen, Alberto Calatroni, Mirco Rossi, Thomas Holleczek, Gerhard Trצster, Paul Lukowicz, Gerald Pirkl, David Bannach, Alois Ferscha, Jakob Doppler, Clemens Holzmann, Marc Kurz, Gerald
    Holl, Ricardo Chavarriaga, Hesam Sagha, Hamidreza Bayati, and Josי del R. Millאn. “Collecting complex activity data sets in highly rich networked sensor environments” In Seventh International Conference on Networked Sensing Systems (INSS’10), Kassel,
    Germany, 6 2010.

    OR:

    [2] Hesam Sagha, Sundara Tejaswi Digumarti, Josי del R. Millבn, Ricardo Chavarriaga, Alberto Calatroni, Daniel Roggen, Gerhard Trצster. Benchmarking classification techniques using the Opportunity human activity dataset. IEEE International Conference
    on Systems, Man, and Cybernetics, Anchorage, AK, USA, October 9-12, 2011 Reference is made to the two papers listed below: Roggen, D. et al. Collecting complex activity data sets in highly rich networked sensor environments Seventh International
    Conference on Networked Sensing Systems, 2010 Lukowicz, P. et al. Recording a complex, multi modal activity data set for context recognition 1st Workshop on Context-Systems Design, Evaluation and Optimisation at ARCS, 2010, 201z

  3. NYC Property Tax Bills
    1. Credit is given to NYC Property Tax Bills.

    2. The work is hosted on : http://taxbills.nyc/

    3. Available under Creative Commons Attribution-ShareAlike 4.0 International Public License: https://creativecommons.org/licenses/by-sa/4.0/legalcode

  4. Parking Data Stream
    1. Credit is given to University of Surrey, UK;

    2. The work is hosted on: http://taxbills.nyc/

    3. Available under Creative Commons Attribution-ShareAlike 4.0 International Public License: https://creativecommons.org/licenses/by-sa/4.0/legalcode

  5. geelong_wi-fi_usage

    Credit is given to the Department of the Primary Industries and Regions, South Australia
    The work is hosted on https://data.gov.au/about.
    Available under Creative Commons Attribution 3.0 Australia
    license: https://creativecommons.org/licenses/by/3.0/au/.

  6. running_app

    Credit is given to StudentLife Dataset
    The work is hosted on http://studentlife.cs.dartmouth.edu/dataset.html#sec:sensing:activity.
    Available under Creative
    Commons Attribution 3.0 Australia license: https://creativecommons.org/licenses/by/3.0/au/.

  7. SMS

    Available under Creative Commons Attribution 3.0 Australia license: https://creativecommons.org/licenses/by/3.0/au/.

  8. GPS

    Credit is given to StudentLife Dataset
    The work is hosted on: http://studentlife.cs.dartmouth.edu/dataset.html
    Available under Creative Commons Attribution 3.0 Australia license:
    https://creativecommons.org/licenses/by/3.0/au/
    .

  9. Wifi

    Credit is given to StudentLife Dataset
    The work is hosted on: http://studentlife.cs.dartmouth.edu/dataset.html#sec:sensing:activity.
    Available under Creative
    Commons Attribution 3.0 Australia license: https://creativecommons.org/licenses/by/3.0/au/.

  10. Gross Income

    The work is hosted on: http://taxbills.nyc/
    Available under Creative Commons Attribution-ShareAlike 4.0 International Public License: https://creativecommons.org/licenses/by-sa/4.0/legalcode

  11. San Francisco Wind Monitoring

    Credit is given to City and County of San Francisco.
    The work is titled SF OpenData.
    The work is hosted on https://data.sfgov.org/browse.

    Available under Creative Commons CC0 1.0 Universal:
    https://creativecommons.org/publicdomain/zero/1.0/legalcode.

  12. Pollution Aarhus Aug – Oct 2014 and Wireless Sensor Data Mining

    The following paper is expressly cited: Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Activity Recognition using Cell Phone Accelerometers, Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor
    Data (at KDD-10), Washington DC.

    Other relevant articles can be found here:

    http://www.cis.fordham.edu/wisdm/publications.php

  13. Default of Credit Card Clients , Bluetooth

    The following paper is cited:

    Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

    The following citation refers to BiBTeX:

    @misc{Lichman:2013 ,
    author = “M. Lichman”,
    year = “2013”,
    title = “{UCI} Machine Learning Repository”,
    url = http://archive.ics.uci.edu/ml,
    institution = “University of California, Irvine, School of Information and Computer Sciences” }

  14. Chicago City Employees

    The following applies to the use of the data set above by the Proov service:

    “This site provides applications using data that has been modified for use from its original source, www.cityofchicago.org,
    the official website of the City of Chicago. The City of Chicago makes no claims as to the content, accuracy, timeliness, or completeness of any of the data provided at this site. The data provided at this site is subject to change at any time.
    It is understood that the data provided at this site is being used at one’s own risk.”

  15. Household Power Consumption

    The following citation applies to the use of the above data set:

    Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School
    of Information and Computer Science.

    {Lichman:2013
    author = “M. Lichman”,
    year = “2013”,
    title = “{UCI} Machine Learning Repository”,
    url = http://archive.ics.uci.edu/ml,
    institution
    = “University of California, Irvine, School of Information and Computer Sciences” }
    A few data sets have additional citation requests. These requests can be found on the bottom of each data set’s web page.

  16. graylog-searchresult

    The following is acknowledged:

    Use of any Information indicates your acceptance of the terms below.
    Proov grants you during your use of the Proov platform and so long as Proov is in beta version, a worldwide, royalty-free, non-exclusive
    license to use the Information, including for commercial purposes, subject to the terms below.
    You are free to: Copy, modify, publish, translate, adapt and use the Information in any medium, mode or format for the purpose of using the Proov
    platform and service for its intended purpose.
    You must, where you do any of the above:
    Acknowledge the source of the Information by including the following attribution statement: Contains information licensed under the Proov license.

  17. call_log

    The following citation applies to the use of the above data set:

    Wang, Rui, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella Harari, Stefanie Tignor, Xia Zhou, Dror Ben-Zeev, and Andrew T. Campbell. “StudentLife: Assessing Mental Health,
    Academic Performance and Behavioral Trends of College Students using Smartphones.” In Proceedings of the ACM Conference on Ubiquitous Computing. 2014.

  18. us_coubty_level_use_2010 , us_county_level_use_2005

    The following citation applies to the use of the above data set:

    Credit: U. S. Geological Survey U. S. Geological Survey/photo by Jane Doe (if the artist is known) USGS/Ft. Collins, CO (if originating office but not the artist is known)
    a
    Additional information is available from USGS Privacy Policy and Disclaimers and Acknowledging or Crediting USGS as Information Source.