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Gen AI applications

Generative AI development is the process of building software that can create new content such as text, images, code, audio, or video using AI models. It includes developing tools like AI chatbots, copilots, content generators, and workflow automation systems. 

Generative AI development services are useful for businesses that want to automate work, improve user experience, or launch AI-powered products. Startups use them to build AI-first MVPs, while enterprises use them to streamline operations, customer support, knowledge management, and internal productivity. 

The cost of generative AI development depends on the scope of the project, the model being used, the amount of customization, and the level of integration required. In most cases, costs can range from around $10,000 for a simpler solution to $100,000 or more for a complex enterprise-grade platform. 

Choose a deep learning framework based on your project needs, scalability, and ecosystem support. Popular options like TensorFlow and PyTorch are widely used for generative AI due to strong community support and flexibility.

The best platforms for generative AI development include cloud-based and API-driven solutions like OpenAI, AI, and Azure AI, AWS, Google Cloud. These platforms provide pre-trained models, infrastructure, and tools to build scalable AI applications quickly. 

Generative AI development covers selecting and integrating a large language model such as GPT-4 or Claude; building RAG pipelines that ground outputs in company data; engineering AI agents for multi-step autonomous tasks; fine-tuning on domain datasets; and deploying safety guardrails. Ailoitte delivers this full stack — from use case validation to production — for enterprise teams across India and Singapore. 

Ailoitte uses four phases: discovery to map use case and data assets; architecture to select the LLM and RAG stack; build and validate with sprint-based development and accuracy benchmarking; deploy and improve with real-time monitoring. InsuranceDekho achieved 80 percent query reduction using Amazon Bedrock with Claude across 8 million policies. Most clients see a prototype in two weeks. 

Generative AI delivers highest ROI for three buyer types: enterprises with large unstructured data assets wanting plain-language AI search; SaaS product teams building AI-native features like intelligent search or content generation; and businesses with high-volume repetitive workflows in customer support, compliance review, or data extraction. If your team lacks LLM engineering depth, contact ailoitte.com/contact-us. 

Simple LLM API integrations are scoped as fixed-price projects — baseline outlined in the free discovery call. Mid-complexity RAG pipelines or AI agents take six to ten weeks on a fixed-scope basis. Complex deployments with compliance integration or real-time inference require a detailed proposal. Book a no-cost 20-minute call at ailoitte.com/contact-us — fixed-price estimate within 48 hours.