Introduction
Generative AI (Gen AI) is no longer a novelty; it has become integral to our daily lives. For enterprises, it presents a golden opportunity—particularly for those who missed the initial AI wave—to leapfrog back into the game with the level playing field that Gen AI offers. As enterprises transition from proof of concept to full-scale production, their expectations from service providers have evolved considerably. They now seek comprehensive Gen AI transformation solutions that deliver across the project life cycle from consulting to deployment and enterprise-wide scaling of large language models (LLM) use cases.
Enterprises are evaluating service providers in three primary areas:
-
- Ready-to-use Gen AI solution accelerators and platforms: Enterprises need prebuilt industry- and domain-specific toolkits and platforms that can dramatically reduce time to market and streamline implementation processes.
- Navigating the ever-evolving LLM landscape: With new LLMs being launched almost daily, enterprises require expert guidance to determine the best fit for their specific use cases.
- ROI evaluation, model management, and monitoring: Companies demand robust frameworks for evaluating the return on investment, managing models efficiently, and monitoring their performance to ensure ongoing value and compliance.
Considering these enterprise requirements, TCS launched TCS WisdomNext™ on May 7, 2024. It is a Gen AI orchestration platform that consolidates all critical Gen AI capabilities into a single, unified solution. Here is a glimpse of all the capabilities TCS WisdomNext™ will offer its clients from a centralized platform.
TCSWisdomNext™: New capabilities
Why do these capabilities matter to enterprises?
-
- Blueprints for industry-specific value chain: Training LLMs on industry-specific nuances is crucial, especially in specialized domains such as healthcare or banking. This training ensures the AI understands the unique terminology and intricacies of the industry, delivering more accurate and relevant outputs.
- Model benchmarking and LLMOps: Most providers now offer model benchmarking and LLMOps capabilities, assisting enterprises in selecting and deploying the most suitable LLM for their specific use cases. This also enables seamless transitions to better-performing or more cost-efficient models as needed. Additionally, LLMOps provides ready-to-use infrastructure for fine-tuning and deploying LLM applications, ensuring that enterprises can rapidly adapt to changing requirements.
- Gen AI workload observability and FinOps: Real-time monitoring and optimization of Gen AI workloads are vital for enterprises to efficiently adapt and scale AI initiatives. These tools ensure cost-effectiveness and performance reliability in the dynamic Gen AI environment, allowing businesses to maximize their investments.
- Multimodal input support: With the advent of GPT-4o, the ability to process diverse data types, including text, images, audio, and video, on a single platform has become paramount. TCS leads in this area with TCS WisdomNext™, the only provider offering built-in multimodal capabilities, facilitating the development and deployment of comprehensive AI applications.
- Built-in horizontal use case support: Supporting a range of horizontal use cases, such as data summarization and code generation, has become table stakes. This capability, particularly advanced in mature domains, reduces the training time required by enterprises and accelerates implementation, enabling faster time to value.
- RAI guardrails: Implementing responsible AI (RAI) guardrails is integral to mitigating hallucinations, incorrect responses, and copyright infringement risks. These guardrails ensure that Gen AI applications comply with enterprise codes of conduct and adhere to industry and regional regulations.
By Chandrika Dutt, Associate Research Director, Avasant, and Abhisekh Satapathy, Lead Analyst, Avasant