AI led Software Engineering: Sopra Steria Offerings

by Jérôme Perdriaud - Head of Smart Application Modernization, Sopra Steria
by Satish Srivastava - Head of Propositions Delivery & Architecture community, Sopra Steria India
| minute read

Sopra Steria has been investing in AI led software engineering in order to help our clients not only reduce cost and gain efficiency but also empower their businesses by making the processes more responsive and scalable. We have strategically focussed our R&D efforts on software engineering for managed services as that’s the phase in which applications are available to business and hence presents us with opportunities to directly impact the business in a positive way. 

Owing to our experience, expertise and the unique ecosystem we have cultivated we think we are in a position to help our clients achieve both efficiency and excellence. Being one of the European leaders in AM space we are managing vast landscapes of IT applications and infrastructure for our clients. Our extensive AM transformation consulting experience enable us to appreciate the fact that quick value realization is vital to acceptance of change and guarantees its success. We are strengthened by our corporate R&D which brings together the innovation power of our engineers to create new tooling and methodology assets to solve concrete day-to-day process or technical issues which don’t have ready-made solutions in the market. We are also helped by our strong relationship with labs, universities and strategic software vendors in order to identify and experiment with new disruptive methodologies or AI tools for digitizing, automating and optimizing the delivery process.

Given below is a brief description of some of the products, IP’s and accelerators we have created:

Alive Intelligence Platform:

Alive intelligence enables developers and support engineers to quickly create a digital assistant capable of engaging in complex interactions on specialized knowledge in a highly personalized way. It is deployed on popular cloud platforms, including OVHcloud, and can aid operational processes e.g. level 0, 1 and 2 customer support, helping support engineers identify potential solution to a problem based on history of similar problems etc. It can also aid in knowledge management processes by helping set up Project Digital academies for accelerating the ramp-up of new employees, helping the stakeholders know all about a newly introduced change in the process. The Alive Intelligence platform brings together various modules to deliver above functionalities: 

  • Dialogue module to enable complex conversation modeling
  • Smart Search for retrieve useful information from document database and other sources
  • IT Support Ticket Prediction module for leveraging machine learning to predict and solve L1/L2 tickets.
  • Document Reader module for converting images to text so that a larger information repository can be used to aid decision making

One of our clients, a worldwide industrial player, performs overnight monitoring assistance with very stringent time-to-resolution requirements using this platform. The Machine Learning-based ticket prediction module improves by 90% the accuracy in the predicated resolutions by allowing the team to select from the top-recommended resolution, and helps save 50% of the effort as compared to the earlier manual process. 

Another client, European ministry of Finance, had a web application with the requirement of handling volume of 100 million invoices per year with user-support solicitations of up to 5 millions suppliers. The above platform helped implement a full 24/7, self-service support, with real time personalised answers, where 75% of the incoming demands were treated automatically with an average trust rate of 75%. The support is highly scalable and cost optimised.

Lagoon is a datalake based tool with rich visualizations for data driven operations improvement. It analyzes data from multiple sources, including ITSM, such as incidents, events, alarms and provide insights. The tool can be used for variety of purposes including project health assessment, SLA assessments, planning for automation, manage team onboarding by assessing learning curves, foreseeing signals of employees planning to leave, team allocations and so on.

Lagoon has helped engagements across sectors in variety of ways e.g. it has helped achieve faster operations through identification of the ticket groups for best candidates for automation. It has led to improvement in over-all quality through analysis of attrition impact on quality and measuring the learning curve of team members. It has also helped achieve capacity optimizations through identification and reduction of costly to manage events.

Digital Enablement Platform (DEP):

DEP helps a project come up to speed very quickly by providing hybrid cloud infrastructure, industrial tools and digital accelerators covering the whole project lifecycle. It comes bundled with an AI enabled Intelligent Observability functionality built on top of Dynatrace  which provides observability features integrated with API management capability. Intelligent Observability can correlate and combine performance and monitoring mechanisms across solution layers such as microservice layer, application layer, platform-as-a-service layer and infrastructure or cloud layer and correlate each of these mechanisms to bring together a global observability solution. The use of AI allows to move from aggregation and correlation approach to causality approach wherein the root cause of an alert can be attributed to events in layers below and enabling the support engineer to take quick action. 

In the next and final edition of this series we will describe some of the relevant offerings from our ecosystem of partners and academia.

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AI led Software Engineering Use cases: Application to Testing, Deployment & Operations

In the previous edition of the series, we have seen how AI transforms the software engineering lifecycle, specifically Management, Requirements, design and development phases. In this edition we will see how subsequent Testing, Deployment and Operations activities are affected by AI.

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