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    Wipro LLM Studio: Solutions, Services & Framework for Customized LLMs

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    Wipro Connected Services LLM Professional Service helps organizations leverage large language models (LLMs) for natural language processing use cases. We support training or fine‑tuning LLMs on domain‑specific data and optimize performance for downstream applications such as information extraction, document classification, question answering, and natural language generation. Our LLM experts work closely with clients to assess, plan, and execute initiatives that enhance workflows, improve outcomes, and deliver advanced natural language understanding, automation, and insights.

    Overview

    Wipro Connected Services LLM Professional Service empowers organizations with deep domain‑specific insights tailored to their industries. For example, HealthGPT is a private LLM fine‑tuned on healthcare datasets such as clinical trial data and medical records.

    The service captures industry‑specific vocabulary, terminology, and concepts while building LLMs based on Responsible AI principles, ensuring data privacy and security for sensitive information.

    Wipro Connected Services leverages a proprietary LLM fine‑tuning framework and methodology to address challenges such as data availability, quality, privacy, security, and model performance. This enables responsible private LLM development while considering technical, ethical, and social aspects.

    Domain‑specific LLM services support use cases including information extraction, document classification, question answering, and natural language generation. Services include end‑to‑end LLM fine‑tuning, robust data generation, automated LLM evaluation, and cost optimization.

    Customized LLMs provide superior language understanding and contextual accuracy compared to general‑purpose models, helping organizations drive innovation and achieve better outcomes across industries.

    LLM Studio Framework & AWS Architecture

    The Wipro Connected Services LLM Studio framework is built on AWS Cloud and leverages AWS machine learning services including Amazon SageMaker and SageMaker JumpStart.

    The fine‑tuning pipeline uses SageMaker JumpStart to train models on custom datasets, while Amazon SageMaker endpoints are used to deploy scalable inference workloads.

    Assessments, Workshops & Implementation

    Through structured assessments, workshops, and collaboration with client stakeholders, Wipro Connected Services AI experts, architects, SMEs, and data scientists identify high‑value use cases, toolchains, and best practices for deploying domain‑specific LLMs.

    Implementation and deployment services use Wipro Connected Services’ proprietary LLM fine‑tuning framework to streamline development, deployment, and production management, ensuring scalability and model efficacy.

    Highlights

    • Tailored, domain‑specific LLM solutions delivering industry‑focused insights
    • End‑to‑end LLM fine‑tuning using proprietary frameworks and methodologies
    • Commitment to Responsible AI with focus on privacy, security, and explainability

    Details

    Delivery method

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    End-to-End Support provided for deployment and usage. Contact AWS.Marketplace@wipro.com  for more information.