Frequently asked questions

Institutional Memory (IM) has been a literary or an academic concept…until now. With our patented technology, we are the first in the industry to genuinely build IM for an organization by creating inheritable communication data sets that ensure continuity of conversations between colleagues and customers. We are also the first to use this IM to provide historical and contextual recommendations to help improve organizational discipline and health.

Current messaging systems (like O365, Google Mail, etc.) maintain hierarchy of existing users for whom they provide messaging services. They do not have provisions to retain data for users who are no longer in the system, except for archival based on their customer’s policies. To provide inheritable Institutional Memory, they would need to make wholesale changes to their core architecture which has significant risks associated with them. Google attempted a new messaging solution with Google Wave which allowed for users to be added post-facto to conversations, but that worked only for users who were still in the system and required the messaging backend to be based on Google Wave alone, making it incompatible with the rest of the messaging industry. Providing IM through contextual keyword based inheritance of business conversation data of a user who has left the organization is being done for the first time in the industry by iMemori. Another point to consider is boundary of data. With Google or Microsoft, the learnings from data analysis from one organization may be applied to another as the centralized ML algorithms would ingest vast amounts of data from across organizational boundaries. Our approach is to deploy the solution within the organization’s IT infrastructure (either on the Cloud or on-premises) where no data leaves the organizational boundary. All information related to IM, analysis, customer information and more is retained by the organization within its boundary. iMemori receives no data from our customers (except feedback and feature requests sent on email).

Our product structure is entirely modular. The core engine of our product is the derivation of Institutional Memory Records, storing them in a form that removes duplication, makes threads inheritable, and their analysis through our AI based analytics engine for effective dashboards and intelligent recommendations. We use the data ingested for maintaining IM to analyze user and organizational behavior. With the analysis, we make business relevant, accurate and timely recommendations to users to improve their daily interaction with organizational systems. Our URECA (User RECommendation Action) messages ensure that a user has one-click access to updates to backend systems like CRM to ensure timely updates on pipeline stages or creation of new opportunities. We provide near-real-time dashboards of key organizational metrics so that the entire management hierarchy of the organization has a clear view of the engagement level in their respective areas. We go deeper by customizing the weekly forecast view for each organization so that the widely prevalent practice of exporting CRM information into csv files and then into Excel pivot tables for managing weekly review meetings is a thing of the past. This unified view bring all the key metrics for both engagement levels as well as backend enterprise systems (like CRM, etc.) for each user under the management hierarchy.

Our ingestion engine uses a custom keyword dictionary which is built by learning from the organization’s data. We continuously evolve our keyword dictionary by understanding what is business relevant to the organization, learning the organizational lingo (in the form of regularly used expressions or acronyms) and flagging potential personal information. Using our Business Language Processing over and above traditional Natural Language Processing techniques ensures that we tag all communications with the appropriate business relevant keywords that ensure that all business communications are properly tagged for inheritance and all personal information is kept confidential to each user. We have also built the capability of an exclusion list for potential users or keywords that may have business sensitive information (for e.g., internal revenue numbers, regulatory reports, etc.) which is not ingested and maintained as part of our solution. By combining our ability to detect business communication only, with the added security of the exclusion list, we ensure that all personal data for a user (including their payroll information, their appraisal history, their reviews and any other information that can be considered personal and sensitive) is not maintained on our platform.

We have mandated the premier law firm of Shardul Amarchand Mangaldas (SAM) to manage our IP protection. They have been with us since inception and worked closely with us to validate, draft and file initial patents in India and, through Lerner David, the premier IP firm in the USA. We have filed for the international PCT (Patent co-operation treaty) that gives us prior art protection in 162 countries. However, as we continue to expand in various geographies, we will continuously be filing individual patents in those geographies to keep our IP rights strongly protected. The current plan is to also file in Europe (incl UK), Singapore, and Australia over the course of 2022.

In the space of Institutional Memory, we have no competition as we are the first and only solution to deliver this functionality. In the space of analytics and dashboarding, there are several players who are working on analyzing communication data. Most, if not all, of them focus on in-flight analysis of communication data with point in time recommendations. None of them provide historical contextual analysis of organizational behavior, mainly because they do not have, and therefore cannot, rely on Institutional Memory. Companies like Gong, re.infer etc. are in the business of analyzing communication data and providing dashboards. Companies like people.ai ingest communication information to look for, update and keep accurate customer contact information in CRM. While most of these solutions are looking at the same data we are, the way they process the information is vastly different. They either provide in-flight analysis of a conversation or provide a specific feature which complements CRM. None of them is designed to be extensible to work with a myriad of backend enterprise systems like CRM, HRMS, ERP, etc.

Our product development strategy has been based on scalable payloads and scalable workloads. Since our entire solution is built on a modular, containerized architecture, we can easily scale the number of components required to provide the consistent level of performance (for ingestion, analysis and visualization) that our customers expect from iMemori. During the pre-deployment assessment phase, we consider multiple factors (such as user count, daily communication frequencies, average communication payload, etc.) to ascertain what would be the best requirement for each organization. Based on initial analysis and testing, we will provide the customer with specific infrastructure requirements to run our solution.

Since our product structure is entirely modular, we intend to allow our customers to choose enterprise application add on modules for their various enterprise systems in additional or organization wide institutional Memory. In the first phase our focus is on delivering multiple use cases to the Sales function through integrating with CRM systems. We will continue to integrate with multiple systems as defined in the roadmap and adding use cases to the organization to provide a very significant value over and above Institutional Memory.

The initial market focus is on enterprises using Microsoft O365 as their primary messaging platform and Salesforce as their CRM. This market alone is of over 50 million Subscribers worldwide and we intend to build out-reach to capture 5 million subscribers in the next three years.

We have developed three pronged sales strategy to be able to cover a global reach. 1. Direct Sales through founders and Sales employees of iMemori technologies. We are directly leveraging years of creating connections in the industry and direct channels to various CxO’s. We have a strong advisory board and founder’s personal connects and industry equity that helps open key doors for these sales. The initial customers we intend to sign on will be from our initial market focus segment in India. After acquiring a few clients directly, we intend to expand to North America and Europe. We have already identified sales heads for both these regions that will come on board at the right time. 2. Individual Affiliates : Individual sales affiliates to be appointed in multiple geographies to sell the iMemori solution working in collaboration with our Sales team in the region These affiliates will generate leads and close them with the help of our direct teams. They will earn recurring commissions on a monthly / quarterly basis. The individual affiliates will form phase 2 of our sales expansion 3. Institutional Affiliates / Partners : We are developing a sales partner ecosystem and based on capabilities of the partner will also build implementation and L1 support capabilities in the partner organization. These organizations will range from large solution provider / system integrator companies to niche software companies selling / implementing technology solutions. We have already identified partners for SE Asia and Africa. These partners will be added in Phase 3

We will follow a rigorous DevOps based development and upgrade philosophy that will ensure that our customers always have the latest AI model as well as the latest enhancements, feature requests and fixes. We will have an integration support team that will ensure that all customizations made for each individual customer is tracked and managed individually.

For General Availability (GA) of our Production ready deployment (v1GA), we have chosen to focus on the Sales module for the O365 messaging solution and the Salesforce CRM ecosystem to provide Sales related intelligence. With v2GA, we will expand the capabilities of the solution to handle other messaging solutions (like Google Mail, etc.) and other CRM solutions (like Dynamics365, Zoho, etc.). With v3 onwards, we will introduce additional modules to interact with other enterprise systems like HRMS (Workday, etc.), ERP (SAP, etc.) and many more.