Code creation process in software development is manual, time, cost and effort intensive. It involves converting large number of wireframes and screenshots created by designers into computer code. Revision and user feedback cycles are slow, wait periods are long between prototypes and many associated tasks are repetitive. The Mphasis AI for Software Development service enables enterprises accelerate the development and deployment of software from cognitive inputs like diagrams, speech, and natural language text by leveraging state-of-the-art generative models.

Assessments & Workshops

Our Assessment and Workshops help clients get started with their AI initiatives specific to software development. This engagement enables clients to plan and identify the relevant problems which could be solved effectively using AI. Assessments are a fast way of identifying if AI is the relevant technology to leverage for solving a problem. In the workshops, the Mphasis AI experts, SMEs, architects, and data scientists work closely with the client stakeholders to understand the software development process. The engagement includes activities such as stakeholder interviews, assessment and user journey workshop, identification of frameworks and tooling, gap analysis, understanding and assumptions, recommendation of solution, and report-out. The typical assessment and workshops exercise is 3-4 weeks. The outcomes of this exercise are a prioritized set of use cases, recommended solution approaches, frameworks and tooling, reference architecture and required infrastructure.

Algorithm Development and Implementation

Algorithms Development and Implementation is a 2–3 month long engagement, where we bring our AI IPs as well as customizations to solve the specific client problems. Our services are powered by patented and patent pending AI/ML platforms and framework such as DeepInsights and Autocode. Mphasis IPs consist of 200+ pre-built and customizable Machine Learning, Deep Learning and Natural Language Processing algorithms. Our IPs helps clients arrive at actionable recommendations faster and provide measurable results across scenarios. Our experience in AI/ML algorithm development and implementation spans several use cases as follows:

• code generation (HTML, CSS, HTML-JET) from hand drawn wireframes and visual designs
• code recommendations for Python, Ruby, Java, etc. from natural language text inputs
• query generation from speech