Our Technology
Conversational AI

Conversational AI refers to the use of chatbots or messaging apps and assistants which automate communication and create some personalized experience for the target customers.

Here, you’ll find some deep experience about what conversational AI is and how can we leverage this for building better people products.

The chatbot platforms helps employees and company HR officials or managers to keep track of every conversations happening and they can use it for their betterment. For HR managers, they can automate the employee information flow and hire people at scale quickly. The communication is taken care by the BOT and HR spends time with more strategic work with the board for the success several vernacular languages.

Vernacular languages are key to tap a larger audience in the employment eco-system across the world. It creates huge data to understand various patterns of employees related to either emotional, behavioural or technical information of the company. For employees, it helps them to interact with the HR managers and other staffs and colleagues at scale.

The technological landscape with a chatbot-agnostic AI solution

Most of the transformation happens when you can play around data and bring it to the uses for the society. With specific to HR, the conversations which are taking place creates huge amount of data that can be leveraged to take key decisions across the board. The conversational are in text, voice. Our aim is to leverage data and use it for people good.

The bot takes queries from you and connect with the enterprise systems to retrieve data and get the necessary information for you. Machine learning plays a key role here which draws patterns and creates data for use. Similarly, we have natural language processing which process large amount of data and draw results from the texts.

The following are key building blocks for the AI technology landscape:

  • Cloud:This solves your storage and deployment issues.
  • Language Technology: The use of NLP makes it very easy to structure and analyse data from a unstructured data and draw patterns and results. It solves the contextual issues.
  • Personal assistants: They help you with your very professional job related and career related queries.
  • Data privacy and security: Companies are very careful when you play around employee data and use it. It poses several challenges during the AI implementation across the company. Data protection awareness is very important, and we need to set up the right governance and guidelines while setting up the AI. These guidelines are not only for technical data but also for legal and ethical issues. When we use training data, we should be careful about the data protection. Design and implementation of AI systems is critical, and we should use it with care. The data should be handled with care from the design phase itself. We should take an universal approach while designing AI systems.
  • AI Audit:
    How to do an AI audit? Studies have found that AI will boost productivity by 38%. If an AI can predict the same and interpret then its going to be very conclusive. Artificial Intelligence is going to be one of the keys for competitive advantage for many.
    While the technology is moving in an unprecedented faster rate, most of the enterprises and leaders are still sceptical about the usage and adoption of AI. Barriers to entry is still high for many.

    • Reviewing current AI systems: AI is useful in many industrial operations, recruitment, payroll, employee benefit programs, transportation etc, but ensuring its design to be bias free is crucial. It is important to highlight every area that AI impacts.

      • The chatbot shouldn’t store any confidential personal information about the employee when we process a request from an employee. All the data should be processed via a secure intranet protocol.
      • We should use the “Training data” for the machine learning usage only and should be secure
    • Training: Employee trust is a big thing and companies and AI implementation agencies should take care of the same. Everyone in the company should know about AI and its potential use cases inside and outside organizations and how it is impacting their lives. This will make them more conscious and vigilant about AI in their day to day lives. IT managers and other key stakeholders should take initiatives to conduct training sessions on AI.
    • Opportunities: Organizations should start small and implement small uses of AI in their organization to experience the impact. Once they are happy about its use then they can go for larger use cases. While doing AI audit, document every idea shared by internal employees, stakeholders for future use. Try to automate small small repetitive tasks in the organization and see the impact and then move towards a larger section of tasks that can be automated.

      Companies should decide about the type of HR data and information that can be shared with employees when they request via conversational AI platform. Companies should be sure about the necessary control’s mechanisms around HR data usage. A wrong information or unauthorised information will lead to wrong decision making and question the development of AI for a company and it is a security and trust issue.
    • Identify the gap: There are two types of solutions that are available in the marketplace. One, ready to use product (SaaS, PaaS types)/ Software as a service or Platform as a service etc. For example- A website chatbot or may be a plugin which can be managed by anyone, no expertise is required. But on the other hand, we have customized solutions which requires certain amount of knowledge and expertise to implement such solutions.

      So, identify your needs and set up a team or train your existing staffs in AI so that they can grow and handle the complex solutions In future.
  • What is next? AI audit gives a ready map to all the business leaders for future navigation. Once the audit gets over, all the involved stakeholders can do internal consultations about the document and take key decisions.
    Every one of us assume that we all know AI but it goes beyond that. This is an evolving process to understand the real uses of AI and the future will tell us.