AI RAG Content Adaptation
iwow delivered a generative AI proof of concept that automated the intelligent adaptation of content to local market standards — achieving the same output quality as a trained specialist while building a scalable RAG architecture and a prioritised AI roadmap for future growth.
The AI solution passed QA checks at the same proficiency level as a specialist employee who has been in training for seven months — applied to complex local standards.
A validated technical foundation built on RAG, vector databases, and FastAPI — ready to scale across additional markets and use cases.
A clear, prioritised roadmap with cost-benefit analysis per use case, giving the organisation a structured path to further AI investment.
The global client needed to accelerate expansion into new markets by efficiently adapting existing content. The core challenge was not simple translation, but intelligently converting content to comply with specific local standards and regulations — for example, adapting materials between countries that speak the same language but have distinct local requirements.
The client required a scalable system capable of delivering high-quality, market-ready content at human proficiency level, along with a clear understanding of the financial implications of such AI investments.
iwow led an end-to-end project using iwow's LEAP methodology to map AI and automation potential and build a tangible Proof of Concept. Using agile methodologies, iwow collaborated closely with both end-users and the IT department to design and develop the solution.
- Used the LEAP methodology to identify and evaluate suitable AI and automation use cases, building a roadmap
- Compared AI platforms against alternative technical solutions to ensure the best fit
- Designed, developed, and integrated a custom generative AI PoC using RAG architecture
- Built a scalable backend using Python and FastAPI with vector database integration
- Implemented automated QA checks for grammar, consistency, and content quality
- Delivered a prioritised roadmap with cost-benefit analysis per use case
- Fully functioning generative AI PoC automating content conversion to meet local market standards
- Directly enables faster, more compliant market establishment in new countries
- Output quality matched that of a specialist with seven months' training — passing all QA checks
- Validated, scalable technical foundation using RAG, vector databases, and FastAPI
- Clear, prioritised roadmap with cost-benefit analysis for future AI investment decisions
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