Mphasis acquires and aggregates to meet CTOs’ AI needs

Mphasis has set up a dedicated artificial intelligence (AI) business unit to provide advisory, engineering, and testing services. The Mphasis.ai unit has three consumers in mind: Mphasis, its customers, and its customers’ end customers. It integrates AI capabilities into an enterprise’s existing technology landscape, offering solutions for its tech stack for enhanced creativity, efficiency, and agility.

Blink acquisition, in-house development, and Mphasis’ partner ecosystem inspired creating the Mphasis AI unit

Mphasis’ AI engineering squads, NextLabs, technical tribes, and account innovation teams (Sparkle) have been building assets in the form of AI models, data sets, libraries, solutions interfaces, patterns, and methods. Mphasis acquired Blink, a user experience research-strategy-design firm, leveraging it to design conversation strategies and build product-specific design languages. As Kore.ai’s only platinum professional services partner, Mphasis has been entrusted with implementing all the features, models, versions, and LLMs of Kore’s product suite targeted at customer and employee experience optimization. The partnership aims to deliver conversational AI solutions to retail, BFSI, healthcare, and travel and hospitality industries. The Kore.ai platform supports digital, cloud, and on-premises deployments in over 120 languages.

Enterprise benefits include improved RFP response, code generation, talent supply chain, and experience

Mphasis has integrated Kore and Infragenie, a Service Now-based service management and automation platform, and it is using AI to transform Wynsure, its insurance policy administration platform. Its other productivity improvement programs include RFP response generation for streamlining the RFP response process with generative Q&A and cognitive search, a Modern Engineering Platform (MEP) integrated with Code Whisperer and Microsoft Copilot to factor productivity and experience improvement during the software development lifecycle, and proofs-of-concept in the talent supply chain, including demand and supply management with skill taxonomy integration.

Mphasis.ai is developing industry-specific models, fine-tuning large language models (LLMs), and providing prompt engineering services to its enterprise customers, built on its foundational AI platform PACE-ML.

The team set a four-month target to deliver claims processing for a healthcare benefits provider

Mphasis.ai has been automating claims processing for a healthcare benefits provider’s customers using available LLM models. It has an ambitious target of delivering a production-ready pilot in four months. Mphasis.ai advises customers on generative AI (GenAI) enterprise frameworks, conversation design, and LLM evaluation and management. It also helps with GenAI tech-stack selection. Its GenAI hackathon-as-a-service is designed to help customers embrace a culture of innovation in AI-driven advancements.

Through its Sparkle acceleration program, it works on innovative solutions for customers while reaching out to generate partnerships with hyperscalers like Google Cloud, AWS, and Microsoft Azure and market leaders like Databricks.

NextLabs offers over 250 prebuilt models on AWS

NextLabs, an AI and quantum computing lab, focuses on incubating industry-agnostic solutions across AI, cognitive, cloud, and service transformation. It has over 250 prebuilt machine-learning models available on the AWS marketplace. NextLab’s Synth Studio is a patent-pending GenAI solution that generates high-quality synthetic data to monetize business insights for enterprise clients. DeepInsights is a patented cognitive intelligence platform that enables enterprises to gain faster and more effective access to insights from data.

Mphasis.ai offerings aren’t limited to GenAI. It is re-imagining numerous archetypes with GenAI focused on contact center transformation, developer productivity, experience transformation, app modernization, business operations transformation, and IT ops transformation.

Mphasis’ talent readiness and productivity improvement programs put it in good shape to support increasing client demand

With its Talent Next framework, Mphasis focuses on the readiness of its talent pool by emphasizing employees’ skill mapping, application capabilities, and personalized learning experiences via an on-demand, next-generation digital platform. The Talent Next learning catalog includes courses dedicated to GenAI, including Azure OpenAI, LLM Overview, and ChatGPT Prompt Engineering for Developers. For example, Mphasis has already trained 500+ people in Azure OpenAI and other GenAI technologies for banking services, wealth management, high-tech, and logistics delivery teams.

The Bottom Line: Mphasis’ AI offering could meet a range of CTO demands—if the team can train and retain.

CTOs should demand interoperability, scalability, flexibility, adaptability, and ecosystem collaboration potential from their service providers. Mphasis has already proven the capabilities of its new business unit in early case studies. Scaling early successes to meet future needs will be heavily dependent on Mphasis’ ability to train, educate, and retain its teams as the demand for AI heats up.