Answers to your questions
How long will it take to deploy?
Once you complete the sign-in, we will get in touch with you and share an implementation plan. Our goal is to keep this process simple and easy to deploy. We want to make sure that we keep complexity and cost as minimal as possible at your end. Depending on the ‘Test&Adopt’ option you choose, it could take anywhere between 3 to 15 days to set things up (subject to availability of all the required information).
How many resources do I need to deploy from my side?
It depends on how involved you want to be and which option you choose. For Basic and Mid Packages, you can simply push the data to us and let us know if you have any specific requirements. We will take care of the rest. For these two options, our suggestion is to use PathosAI cloud to store the data (please see our privacy practices below). If available, we can host it on a cloud server in your geographical location. Local/On-premise hosting may not only entail incremental deployment cost, it may also take additional time. We do encourage that you assign a program owner. We do not foresee the program manager spending more than a few hours.
Where is your cloud server?
We use Google cloud, which is globally recognized and has presence in several countries. Depending on your location, we can check if Google has a server in your country.
Can you deploy on my local/on-premise server?
While it’s technically possible, we do not recommend doing so in the Basic and Mid Packages. We can, however, deploy it, if it’s a prerequisite. However, do keep in mind that it may entail incremental cost.
What data privacy and security protocols do you deploy?
Privacy is our priority. It is only natural that we focus on providing the highest degree of confidence to ensure that the data that runs through our ecosystem is kept anonymous and secure. We are not interested in identifying the identity of anyone whose voice, image or conversation we measure. None of our models are dependent on using any PII. We analyze and report aggregate numbers. We also encourage the clients we work with to pass on only the relevant information to us. If they are unable to separate the information, we mask all the PII related data fields when it enters our ecosystem.
Our privacy and security focuses on the following key pillars:
1. PII:We may receive some personally identifiable information from time to time. If we do, our machine learning driven security protocols immediately mask any personally identifiable information.
2. Access controls: We have implemented industry compliant access control protocols to restrict access to the platform and its various sites on need to access basis. We have defined clear roles for developers and users that dictate the types of data and other information each can view and edit. At no time, do we allow data mirroring or copying or taking data out of our platform.
3. Data storage policies: We store data on the cloud for enough days to ensure that the insights are delivered and relevant, which is per global standards. Our main reason for holding data in the first place is to ensure that we can provide sufficient traceability and audit so that, if requested, our clients and other independent reviewers can validate the outcomes we are producing, as is the usual practice in the industry.
4. Use of data: We have a strict guideline around use of data. We will act as trusted custodians of data. It will not be used for any purpose other than what we have laid out publicly. We do not sell data to any third party or use it for any marketing purposes.
5. Consent: We only receive data from our clients, which they agree that they have the right to use. In case we use any third party data source, like social media, we follow the required protocols to legally obtain that information.
6. Audit: While we make our best efforts to achieve the above objectives, to show our commitment, we will undertake periodic third party audits.