Cloudesign's LLM-powered systems go beyond simple automation by interpreting context and generating human-quality documentation, code, and analysis. Our specialised AI consultancy transforms static data into active growth, empowering teams to reclaim up to 80% of manual processing time through advanced generative reasoning and creative synthesis.
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CASE STUDY
A technology-enabled services company with distributed support, sales, and delivery teams managing multiple enterprise products and service offerings. Teams frequently needed quick access to internal documentation, process guidelines, and technical knowledge to support customers and internal operations.
Optimising AI architecture and monitoring token usage to ensure cost-efficient, scalable, and sustainable custom LLMs.
Implement AI models and applications that automate workflows, generate insights, and drive predictive decisions.
Tailored AI strategies and deployments that grow with your business, from startups to enterprises.
Seamless deployment on AWS and other cloud platforms with enterprise-grade security and compliance.
Transform data and AI outputs into actionable insights, measurable ROI, and business growth.
End-to-end delivery from AI strategy to deployment and continuous optimisation for long-term success.
We use foundation models, orchestration frameworks, vector databases, cloud infrastructure, and model customisation tools based on the requirements of each solution.
We select and integrate models based on latency, cost, reasoning capability, security, and deployment requirements.
Our AI staff augmentation delivers the LLM, Computer Vision, and NLP expertise needed to modernize applications and eliminate technical debt. We provide the hands-on talent from data labeling to MLOps to drive peak performance across your AI ecosystem.
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Generative AI with Large Language Models (LLMs) combines generative models with natural language capabilities to create, analyse, summarise, and transform information. Cloudesign uses LLMs to build enterprise applications such as AI assistants, knowledge systems, document intelligence solutions, and workflow automation tailored to business data, processes, and security requirements.
Three widely adopted Generative AI platforms are OpenAI, Google Gemini, and Anthropic Claude. Each offers different model capabilities, pricing, context windows, and integration options. Cloudesign evaluates foundation models based on the specific business use case, data requirements, security considerations, performance, latency, and deployment environment rather than relying on a single model.
Generative AI creates new content, including text, code, images, summaries, and documents, based on learned patterns and provided context. Cloudesign helps businesses apply Generative AI to enterprise search, document processing, customer support, knowledge management, software development, research, and workflow automation through purpose-built AI applications and integrations.
Cloudesign follows a use-case-driven approach covering AI strategy, data assessment, model selection, solution architecture, application development, evaluation, security, and production deployment. Depending on the requirement, Cloudesign can implement RAG, vector search, AI agents, model customisation, API integrations, and LLMOps capabilities to support reliable enterprise Generative AI applications.
Yes. Cloudesign can integrate LLM applications with enterprise systems such as SAP, Salesforce, Oracle, Microsoft Dynamics, databases, APIs, and legacy applications. Integrations can connect enterprise data and workflows to AI applications while incorporating authentication, access controls, data protection, and governance appropriate to the organisation's technical and regulatory requirements.
Retrieval-Augmented Generation (RAG) connects an LLM to relevant enterprise information before generating a response. Cloudesign uses RAG architectures, vector search, embeddings, metadata filtering, and retrieval pipelines to ground responses in approved business data. This approach can improve relevance, traceability, and knowledge access while reducing reliance on model training data alone.
Yes. Cloudesign develops AI agent solutions that can connect LLMs with business tools, APIs, databases, and defined workflows. Depending on the use case, agents can retrieve information, perform multi-step tasks, trigger actions, and involve human review where required. This enables organisations to automate knowledge-intensive processes while maintaining appropriate controls.
Cloudesign incorporates security and governance throughout the AI development lifecycle. Solutions can include controlled data access, authentication, encryption, prompt and output safeguards, retrieval controls, monitoring, and evaluation frameworks. For regulated environments, the architecture can be designed around applicable security, privacy, compliance, and data-governance requirements.
Cloudesign's Generative AI capabilities can support industries such as BFSI, healthcare, manufacturing, retail, logistics, and professional services. Potential applications include document intelligence, enterprise knowledge assistants, customer support, research, reporting, information retrieval, and workflow automation, with the solution architecture adapted to each industry's processes, data environment, and governance requirements.
Cloudesign begins by assessing the business problem, potential AI use cases, available data, existing systems, security requirements, and expected outcomes. The engagement can then progress through solution architecture, model selection, prototyping, evaluation, and production deployment. This approach helps organisations prioritise practical Generative AI opportunities before investing in larger-scale implementation.
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Cloudesign Technology Service Pvt Ltd is an enterprise software and AI consulting firm founded in 2015 in Bengaluru, with offices in Bengaluru and Mumbai.
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