Sponsored Content 10 December 2019
EdgeVerve Systems Limited is a wholly-owned subsidiary of Infosys Limited. We help clients across the globe navigate their digital journey and drive business value through AI, Intelligent Automation and AI-enabled suite of products.
We have three different product lines:
AssistEdge is one of the leaders in the RPA product marketplace and offers a cohesive automation platform that enables enterprises to scale in their automation journey. It offers enterprises to drive initiatives around process discovery, intelligent automation and digital workforce orchestration. AssistEdge has helped organizations scale their automation initiatives seamlessly and unlock value in the form of reduced service time, faster sales cycles, better resource allocation, accelerated revenue recognition and improved efficiency, among others.
Infosys Nia is an enterprise-grade AI platform which simplifies AI adoption and helps Industrialize AI deployments for businesses and IT. Infosys Nia supports the end-to-end AI journey of an enterprise from data management, digitization of document and images, model development to operationalizing models.
Nia AIOps brings the power of AI to IT operations using the Nia AI platform. It employs powerful pre-built AI models that can predict IT anomalies, correlate events in the system, undertake faster root cause analysis, and ultimately lead to a more resilient organization.
Nia DocAI is an AI-based solution which leverages Computer Vision, NLP and Search for harvesting intelligence from enterprise documents to accelerate your digital transformation journey.
Business Applications are ready-made Plug-n-Play AI-enabled applications that integrate seamlessly into the existing IT infrastructure, to address highly specific business challenges to a particular domain and drive connected intelligence across the value chain to help enterprises transform into a data-led business.
AI Business caught up with Atul Soneja, senior vice president and global head of edge products and Infosys Nia, to find out more about EdgeVerve’s AI-based offerings.
Q: You have spent a large part of your career overseeing products for the financial services market. Why did you decide to get involved in automation and machine learning?
A: I have spent over 24 years working in IT, driving business transformation through focused execution, often in challenging and competitive markets. Across industry segments, clients are looking to drive business value, efficiency and cost take out as part of their digital transformation journey. AI and Automation are at the heart of this digital transformation.
In my erstwhile role of managing global delivery for financial services for Infosys, I was already leveraging AI and Automation based solutions for our clients. Leading an organization like EdgeVerve, that focuses on helping clients on their business transformation leveraging AI and Automation products, is in every leader’s wish list.
Q: How are you helping your clients realize value out of their AI investments?
A: In my conversation with CXOs across industry segments, there are four big challenges that I see:
- Moving beyond the initial hype and PoC to enterprise-wide AI and Automation adoption;
- Identifying the right use cases that will deliver business value across the enterprise;
- Data Strategy — How to make the humongous amount of structured and unstructured data to provide business insights;
- Overcoming the talent shortage in the industry for capabilities like model engineers, UX designers, model architects, etc.
We have been able to overcome these challenges by leveraging our product suite. AssistEdge suite of products take our customers across their automation journey; from process identification, to attended and unattended automation, cognitive automation and orchestrating the digital and human workforce.
Leveraging Infosys Nia, our AI platform, we have been able to solve complex business problems. Nia provides a simplified way to take your projects from experimentation to production — deploying models at scale, monitoring them, tracking and explaining predictions, and facilitating collaboration among different stakeholders in the process.
Leveraging our bets on Business Apps, we have been able to take away the pain of identifying the right use case, the choice of a technology platform and a change management framework by bringing in AI-powered industry-specific business solutions.
Q: Nia is a major player in the emerging AIOps software category, which applies machine learning to IT infrastructure management. Why is there a need for AI in this space?
A: According to me, the three most important reasons are:
- Customer Experience: We are already in the next phase of “information age” and have moved to the “experience age”, where brand loyalty is not very high. It is easy to lose customers based on a couple of bad experiences.
- Complex IT Applications and Multiple Monitoring Tools: Complex IT application landscape makes monitoring and management very complex. Multiple monitoring tools and non-standard reporting makes it difficult to access the business impact of incidents.
- Past resolutions and inferences to solve similar incidents: A Subject Matter Expert (SME) might have resolved an issue in the past. Now, in the organization, we do not have visibility to the resolution in a normal setup. Hence, we are dependent on the SME to solve similar issues. This increases the dependency of the organization on the SME. AIOps will help in identifying that particular resolution in the past that solved a similar issue and share the details with the person who will resolve it.
Nia AIOps brings the power of AI to IT operations using the Nia AI platform. It employs powerful pre-built AI models that can predict IT anomalies, correlate it with other unrelated events in the system, undertake faster root cause analysis, and ultimately lead to a more resilient organization. Nia AIOps enables organizations to track business metrics rather than merely focus on traditional machine metrics. The platform thereby allows IT to be in sync with the organization’s business agility needs.
Let me highlight a couple of case studies:
A large European Bank, for instance, improved their operational efficiency in IT services management by using AI to automate their L2 support.
Benefits: 90% improvement in MTTR (Reduce Mean Time To Repair) | 90% Reduction in IT operations efforts.
A leading Communications Provider accelerated business benefits by automating 7+ business lines across the company. Nia helped increase business agility, control operating cost, and enhanced efficiency in developing new services.
Benefits: $1M cost reduced in 5 quarters and 85% reduction in manual efforts.
Q: Do you think the future of machine learning workloads belongs in the public cloud, or specialized on-premises data centers?
A: The key decision points are related to the sensitivity and locality of data being used to create the workloads in the first place. Another aspect that needs to be kept in mind is the risk appetite of an enterprise, which is modulated by the regulatory requirements, including auditability and explainability needs that might be different depending on the geography. While it’s too early to tell, enterprises will likely shift workloads that are based on less sensitive data to the public cloud while keeping the mission-critical, sensitive workloads on-prem as per the regulatory requirements.
Q: Late year, EdgeVerve launched a free version of its AssistEdge platform for students and developers. Why did the company do this, and what do you think about the response?
A: There is a significant gap between the demand for RPA experts and the supply. Enterprises are trying out different strategies to narrow this gap. At EdgeVerve, we are trying to bridge this gap between demand and supply. Also, skill and re-skill the human workforce. To achieve this, we have released a community version of AssistEdge to anyone who wants to use it, and train on it. The company has evangelized this in universities and colleges, in the hope that more programmers will use it and help create a mass of RPA-ready potential recruits.
Q: How will AI and RPA impact enterprises in the next 3-5 years?
A: The way I envisage, Automation and AI are influenced by the belief that they are converging to a large extent. AI is enabling automation to become smarter and is increasingly moving from efficiency to effectiveness. AI-enabled automation is already here. The current version of AssistEdge in the market offers cognitive automation. In the future, this cognitive automation will be available on tap, and different products and services will be available on the cloud. Down the road, it will be commonplace for clients to use products and services from multiple vendors, and this will entail an integrated control view of all the digital workflows within the clients’ technology ecosystem. Correspondingly, security measures will have to be much stronger. These are some of the areas that we perceive will change.
Meet the EdgeVerve team at the AI Summit New York, Javitis Center, Booth #524, on December 11-12.