Case Study

Marketing with GenAI and AWS: Scalable Video Personalisation for a Global Jewellery Brand

To meet the growing demand for high-impact, personalised digital content, the marketing team of a globally renowned heritage jewellery brand partnered with Data Reply to transform how diamond product videos are created and delivered online.

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PRIVACY

I declare that I have read and fully understood the Privacy Notice and I hereby express my consent to the processing of my personal data by Reply SpA for marketing purposes, in particular to receive promotional and commercial communications or information regarding company events or webinars, using automated contact means (e.g. SMS, MMS, fax, email and web applications) or traditional methods (e.g. phone calls and paper mail).

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The cHALLENGE

Reimagining the digital showroom for an emotional purchase

For a brand built on heritage, craftsmanship and trust, every digital interaction must uphold those same values. As luxury customers increasingly research and shop online, the marketing team sought a way to elevate the digital experience to match the emotional weight of an in-store purchase.

Their goals were clear:

  • Personalise content rapidly across markets and seasonal campaigns

  • Automate video production without compromising quality or brand alignment

  • Deliver consistent, premium visuals that reflect the brand’s identity and legacy

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The SOLUTION

Generative AI meets AWS for content transformation at scale

We designed and deployed a custom AI-powered pipeline on AWS to transform raw product footage into polished, campaign-ready videos—within minutes, not hours. This marketing-focused toolset automates video background replacement using advanced computer vision and Gen AI.

Core Solution Features:

• Diamond segmentation using Gen AI to isolate product visuals

• Automated rendering to apply campaign- or brand-aligned backdrops

• Full orchestration on AWS, ensuring scalability, speed, and security

The solution was built entirely on AWS, using a scalable, serverless-first architecture. Amazon SageMaker was used to deploy generative AI models from Hugging Face for video segmentation and object tracking, with orchestration handled by AWS Lambda. Rendering workflows were managed through AWS Batch and Amazon ECS, ensuring high performance at scale.

The Results

Smarter marketing. Stronger storytelling. Faster production.

Operational efficiency

Significant reduction in manual editing time and cost. 3 to 6 minutes per video and £0.08 per unit.

Creative agility

Rapid personalisation for seasonal and regional campaigns

Brand consistency

Premium visuals that reflect brand identity at every touchpoint.

Scalability

Delivers seamless scalability for high-volume campaigns, powered by serverless technologies. Fully secure. Fully scalable. Production-ready.

Bring AI into Your Marketing Stack.

With AI first mindset, we help marketing teams unlock new creative possibilities— combining brand storytelling with automation and personalisation at scale.

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PRIVACY

I declare that I have read and fully understood the Privacy Notice and I hereby express my consent to the processing of my personal data by Reply SpA for marketing purposes, in particular to receive promotional and commercial communications or information regarding company events or webinars, using automated contact means (e.g. SMS, MMS, fax, email and web applications) or traditional methods (e.g. phone calls and paper mail).

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Data Reply

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Data Reply is the Reply group company offering a broad range of advanced analytics and AI-powered data services. We operate across different industries and business functions, enabling them to achieve meaningful outcomes through effective use of data. We have strong competences in Big Data Engineering, Data Science and IPA; we build Big Data platforms and implement ML and AI models in a manner that is repeatable, efficient, scalable, simple and yet secure. We supports companies in combinatorial optimization processes with Quantum Computing techniques that enable an engine with high computational performances.