How AI Transforms Product Support Through Digital Passports

Every product scan is a moment of intent. A consumer picks up your product, opens their camera, and scans the code. They want something — care instructions, warranty information, authenticity verification, or help with a problem.

Today, we're launching AI Product Support — a feature that turns every Digital Product Passport into an intelligent support agent for your brand.

The Problem with Traditional Product Support

Traditional product support is broken in predictable ways:

• Search-based FAQs require customers to know the right keywords
• Support tickets have response times measured in hours or days
• Phone trees frustrate customers before they reach a human
• Generic chatbots give generic answers that don't account for the specific product

The result: customers abandon the support flow and either return the product, leave a negative review, or lose trust in the brand.

How AI Product Support Works

When a consumer scans a product's QR code, they land on its Digital Product Passport. If they have a question, they can simply ask — in natural language.

Our AI processes the question against the product's actual data:

1. Product specifications — materials, dimensions, components
2. Care instructions — washing, storage, maintenance schedules
3. Warranty details — coverage period, what's included, claim process
4. Troubleshooting guides — common issues and step-by-step fixes
5. Sustainability info — recycling instructions, end-of-life options

The AI doesn't hallucinate or guess. It's grounded in the structured data within the DPP, supplemented by brand-provided documentation. When it can't answer confidently, it hands off to a human agent with full context of the conversation.

Real Examples

Care Instructions

Customer scans a wool sweater:

"Can I put this in the washing machine?"

AI responds using the product's care data:

"This sweater is 100% merino wool and should be hand-washed in cold water (max 30°C). Machine washing, even on a delicate cycle, can cause shrinkage. Lay flat to dry — avoid hanging, which can stretch the fibers."

Warranty Claim

Customer scans a kitchen appliance:

"The motor stopped working after 8 months. Is this covered?"

AI responds using warranty data:

"Your KitchenPro 3000 has a 2-year warranty covering manufacturing defects, including motor failure. Since you're within the warranty period, you're eligible for a free replacement. Would you like me to start a warranty claim?"

Sustainability

Customer scans a pair of sneakers:

"How do I recycle these when I'm done with them?"

AI responds using end-of-life data:

"These sneakers are part of the TakeBack program. You can drop them off at any participating retail location for recycling. The rubber sole is separated and ground into playground surfacing, and the textile upper is recycled into insulation material."

The Technical Architecture

AI Product Support is built on three layers:

Retrieval Layer

We index all structured DPP data plus any supplementary documents (PDFs, knowledge base articles) the brand uploads. When a question comes in, we retrieve the most relevant context.

Reasoning Layer

The AI model processes the question against the retrieved context, generating an answer that's accurate, helpful, and on-brand. We use constrained generation to prevent the model from inventing information not present in the source data.

Handoff Layer

When confidence drops below a threshold, the system seamlessly transitions to a human agent. The agent sees the full conversation, the product data, and the AI's reasoning — so the customer never has to repeat themselves.

Results from Early Access

Brands in our early access program have seen significant improvements:

• 73% of questions resolved without human intervention
• Average response time under 3 seconds (vs. 4+ hours for email support)
• 41% reduction in product returns due to better care guidance
• NPS improvement of 18 points for post-purchase support interactions

Setting It Up

AI Product Support activates automatically for any product with a DPP on Veribl. The AI uses your existing passport data as its knowledge base. To improve responses:

1. Enrich your DPPs — the more structured data, the better the answers
2. Upload supplementary docs — user manuals, care guides, FAQs
3. Review AI conversations — flag incorrect answers to improve the model
4. Customize the tone — set brand voice guidelines that the AI follows

What's Next

We're working on proactive support — where the AI reaches out to customers based on product lifecycle events. Imagine your product passport notifying a customer when it's time for maintenance, when a recall affects their unit, or when a recycling program launches in their area.

The DPP isn't just a compliance document. It's a living connection between brands and customers.