Making Products Smarter: AI-Enabled Digital Product Passports

How Spherity’s VERA Digital Product Passports Revolutionize Customer Engagement, Value-added Services, and Circularity — Learn About Our AI-DPP Strategy and “MCP Server” Implementation

TL;DR:

From static to smart: Spherity transforms DPPs from passive data stores into dynamic, AI-interactive systems using the Model Context Protocol (MCP). Learn first hand about our DPP-MCP-Integration.

Standardized AI integration: MCP enables AI assistants to securely query real-time product data (e.g., state-of-health, carbon footprint) and return verified, contextual responses.

Verified data for trustworthy AI: AI responses are based on signed, verifiable credentials stored in VERA DPPs — minimizing hallucination and boosting trust.

Powerful use cases:

• Compliance automation (e.g., EU Battery Regulation, ESPR)

• Predictive maintenance & lifecycle optimization (e.g., EV batteries)

• Enhanced customer engagement (e.g., Smart Wardrobe Assistant for textiles)

• Intelligent interfaces for consumers, regulators, retailers, and recyclers

Real deployments:

✅ Electric Trucks: AI-assisted fleet monitoring & compliance.

✅ Smart UPS: AI-generated insights for sustainability claims and battery flexibility aggretion (a.k.a. virtual batteries).

✅ Fashion Circularity: AI provides super rapid prototyping for value discovery and explains textile origin, recycling, and resale guidance.

Spherity’s AI integration capabilities:

• Operates MCP server modules to connect GenAI models (Claude, GPT, etc.) with DPPs

• Supports flexible deployment (on-prem, cloud), aligned with enterprise IT environments

• Provides verified, privacy-filtered data via signed credentials and robust access control

Spherity’s commitment:

• Actively enabling GenAI-ready product data ecosystems

• Partnering with OEMs, energy firms, fashion brands, and recyclers

• Ensuring governance, interoperability, and verifiability in every AI use case

👉 Spherity is your trusted partner for integrating verified DPPs with AI. The result: smarter, compliant, and more circular products — powered by VERA + MCP.

Bringing AI to Digital Product Passports - with Model Context Protocol, products become smart, compliant, and proactive. Source: Spherity GmbH

1. Introduction: Spherity’s GenAI-Ready VERA DPP Solution

Spherity’s VERA Digital Product Passport (DPP) platform is a cutting-edge solution for creating, managing, and sharing verifiable product data across supply chains. VERA is built on CEN/CENELEC JTC24 standards, CirPass2 guidelines, and decentralized identity technologies (W3C Decentralized Identifiers and Verifiable Credentials).

Spherity just introduced a new integration of a Model Context Protocol (MCP) Server into VERA, effectively making the platform “GenAI-ready.” MCP is an emerging open standard that provides a universal, secure way to connect AI agents with enterprise data sources. By embedding an MCP Server, VERA’s verifiable product data can be accessed and queried in real-time by AI-powered tools through a standardized API, rather than custom one-off integrations. This opens the door for generative AI use cases to become a core part of our customer’s product data sharing strategy.

How MCP Enables Generative AI: Traditionally, DPPs have been static repositories focusing on compliance and transparency. Spherity’s vision is to evolve DPPs into dynamic, interactive systems that can drive real-time optimization and automation.

• MCP Server bridges VERA DPP data with AI tools for two-way communication.

• AI assistants (chatbots, analytics) query real-time DPP data via MCP.

• MCP securely retrieves data (origin, composition, usage, certifications) for AI context.

• Ensures AI responses are accurate, verifiable, and up-to-date.

• Reduces AI hallucinations and increases reliability.

VERA + MCP transforms the DPP from a static data vault into a GenAI-integrated platform capable of powering chatbots, analytics, and automated workflows across the product lifecycle.

Spherity is already using Gen AI for rapid prototyping of DPP templates, UI profiles, and entire DPPs. With just a few prompts, generative AI can quickly produce research for specific product categories, generate detailed DPP product specifications, and even support the corporate identity/corporate design of customized DPP micropages for serialized products. Our GenAI capability accelerates value discovery for DPPs, incorporating rapid stakeholder and user feedback into DPP designs.

Beyond MCP, Spherity is actively working on the integration of protocols such as Google’s Agent-to-Agent (Agent-2-Agent) protocols with the VERA DPP platform. This enables secure and reliable exchange of DPP data directly between AI agents. However, in this article, we primarily focus on the MCP integration.

Spherity’s focus on generative AI integration aligns with broader industry trends. Experts envision DPPs shifting from passive databases to AI-driven “Insight Engines” and “μERP” systems, where real-time data and AI analytics optimize customer experience, supply chains and product lifecycles.

Spherity 2x2 Matrix of DPPs shows the progression from static data repositories (Data Vault) to dynamic, real-time systems (Insight Engine, Cyber-physical μERP with full automation & lifecycle management. Source: Spherity GmbH

For example, AI can help predict maintenance needs, optimize recycling processes, and provide intelligent customer support using DPP data. By adopting MCP, Spherity is explicitly positioning VERA to support these advanced use cases. Generative AI applications are now central to VERA’s roadmap.

2. DPP Regulatory Landscape: EU ESPR and Battery Regulation

The EU’s regulatory landscape is rapidly making Digital Product Passports (DPPs) mandatory across multiple sectors, significantly impacting manufacturers and supply chains.

• EU Battery Regulation: From February 2027, industrial and EV batteries (>2 kWh) require Digital Product Passports covering standardized data on composition, performance, carbon footprint, safety, and recycling, using decentralized identities and cryptographic security.

• Textiles (ESPR): By early 2027, garments and footwear sold in the EU must have digital passports providing data on material composition, hazardous chemicals, and sustainable sourcing to enhance recycling and resale.

• Tyres (ESPR): Digital passports for automotive tyres, mandatory around late 2028 or early 2029, will document material composition, performance metrics, and recyclability, aligning with chemical safety regulations.

• Metals/Electronics (ESPR): By approximately 2028, digital passports for steel, aluminum, and electronics will include recycled content, environmental footprint, hazardous substances, repairability, and recycling information to address sustainability and e-waste.

• Furniture (ESPR): Digital passports for furniture, mandatory around 2029–2030, will detail material sourcing certifications, durability, repair options, and end-of-life recycling instructions to extend product lifespans and minimize waste.

3. Supported Product Categories in VERA DPP

VERA’s flexibility allows it to handle Digital Product Passports for various product types using customizable data models and pre-defined compliance templates for each DPP product category. Below are the main categories currently supported, with particular emphasis on regulatory priorities:

• Automotive Batteries (EV Batteries): VERA supports EV Battery Passports compliant with EU regulations, capturing manufacturing data, materials (e.g., cobalt), performance metrics, and recycling information. Passports use real-time battery management data to facilitate second-life usage and end-of-life recycling.

• Stationary Batteries (Energy Storage & UPS): VERA documents technical specs, maintenance records, compliance data, and environmental metrics (e.g., CO₂ footprint) for stationary battery systems, enabling regulatory compliance and enhanced asset management.

• Textiles & Fashion: VERA enables digital passports detailing material origin, sustainability certifications, care instructions, and recycling options. These passports improve transparency, consumer engagement, and regulatory compliance, supporting anti-counterfeiting and circular economy practices.

• Electronics & Electrical Equipment: VERA creates passports documenting material composition, hazardous substances, energy efficiency, repairability, and recycling instructions. This helps manufacturers comply with emerging regulations, reduces e-waste, and increases product lifecycle transparency.

• Furniture: VERA supports digital passports for furniture, including material sourcing, durability, repair options, and recycling guidance. Furniture passports facilitate compliance with ESPR mandates, encourage circular economy practices, and enhance customer confidence in sustainability claims.

Explore the infographic below to discover more about the use cases we support. It outlines representative DPP use cases supported by Spherity’s VERA, across four dimensions: Compliance, Value-Added Services, Customer Engagement, and Circular Economy (R-strategies).

4. Technical Architecture: Integrating the MCP Server with VERA

Spherity’s VERA DPP system is built with an enterprise-grade architecture that prioritizes security, interoperability, and scalability. The integration of the MCP Server into this architecture extends these principles to generative AI interactions. In this section, we describe the technical components and workflows involved, including API interfaces, data flow, and how authentication, authorization, and data privacy are handled.

System Architecture Overview: VERA’s core architecture consists of a cloud-based platform that manages decentralized identities, verifiable credential issuance, and data storage for product passports. Each product (or batch of products) is represented by a DID (Decentralized Identifier), and its passport data is stored as a set of claims or credentials (e.g. JSON-LD credentials) which can be digitally signed by the issuer (manufacturer or supplier) and stored in an Enterprise Identity Wallet. On top of this, VERA exposes a suite of RESTful APIs for various operations — creating a DPP, updating data, exchanging credentials between partners, querying a passport, etc.

Additionally, our platform provides robust role-based and attribute-based access control mechanisms, ensuring distinctive and precise control over data access during MCP client integration. MCP handles authentication using OAuth tokens, allowing secure and seamless authorization of MCP clients. These tokens can be issued to MCP clients, effectively granting specific access rights and ensuring that only authorized system users (MCP clients) can interact with the VERA DPP data and services. This approach enhances both security and flexibility, aligning with enterprise-grade standards for data protection and privacy.

Into this setup comes the Model Context Protocol (MCP) Server — conceptually a middleware component that “sits next to” the VERA APIs and data stores. The MCP Server implements the open MCP specification, serving as a gateway for AI agents to interact with VERA. Rather than AI applications calling VERA’s APIs directly (which would require custom logic for each AI integration), they communicate with the MCP Server using the standard protocol (e.g. through an MCP client library). The MCP Server is configured to know how to fetch and interpret data from VERA. This typically involves connectors or adaptors: for example, an MCP Server module might use VERA’s API credentials to query the product passport database when an AI query about a product comes in. The architecture thus includes:

• MCP Client (AI side): This is part of the AI application (could be an AI assistant like Claude or ChatGPT, or an autonomous agent) that formulates requests in MCP format. The client could be integrated into an AI platform — for instance, Anthropic’s Claude and some Microsoft/OpenAI tools support MCP connectors natively.

• MCP Server (VERA side): Deployed as a secure service within Spherity’s environment (or on the client’s premise if needed), this server receives requests from the AI agent and acts upon them. It encapsulates the logic for context handling, authentication of the AI agent, query translation, and response formatting.

• VERA APIs/Data: The MCP Server interfaces with the existing VERA system — it might call an internal service or database query to retrieve DPP data (such as all data fields for product X, or specific info like “battery state of health” depending on the query). VERA’s microservices (credential registry, wallet, etc.) remain the source of truth for the data.

API Interfaces and Data Flow: The interaction sequence typically works as follows:

1. AI Client Request: An AI-driven application (e.g. a chatbot) triggers a request for data. In practice, this could be a user asking, “What is the carbon footprint of this product?” via a chat interface. The AI model, recognizing it needs external data, formulates an MCP request to the MCP Server. This request includes the query (e.g. “GET carbon_footprint for product_id 12345”) and context like the user or session ID, and any access token the AI has.
   

2. Context & Session Management: The MCP Server receives the request and first validates the session and the caller. It checks “Who is the (system) user and what access rights do they have?”. This is crucial — the MCP server enforces that the AI agent (on behalf of a user or organization) only accesses data they’re authorized to see. It forwards the request received from the MCP client directly to the VERA API. The VERA API itself performs the validation, ensuring that only authorized users — AI agents or otherwise — can retrieve the data they have permission to access. The MCP Server thus relies on VERA’s existing security groups and roles feature. For instance, a recycler agent might have permission to query end-of-life instructions but not proprietary design data. Similarly, an authorized MCP client can create specific DPP types, such as passports for regulated or sensitive products. By forwarding the request as-is, the MCP Server leverages the robust security framework already implemented in VERA, avoiding redundant access control checks.
   

3. Protocol Processing & Query Planning: The MCP Server securely exposes predefined VERA API endpoints as standardized tools, allowing authorized MCP clients to interact seamlessly with Digital Product Passport (DPP) data. The MCP client (AI agent) interprets user queries, translating natural language requests into structured MCP tool calls. For example, a request like “What is the carbon footprint of product 12345?” is converted by the AI client into a structured request invoking the appropriate VERA endpoint. The MCP Server itself acts as a secure API gateway, forwarding these structured requests directly to the VERA API. It relies entirely on VERA’s existing role-based and attribute-based access control mechanisms, ensuring secure, validated API interactions. No direct database or SQL queries are permitted, maintaining strict data security. Additionally, to facilitate advanced query planning, multi-step processing, and combined structured/unstructured data integration, Spherity is developing an end-to-end Agent Infrastructure. This infrastructure enhances MCP clients’ capabilities for research, decision-making, rapid DPP prototyping, template generation, and comprehensive data management.
   

4. Backend Data Retrieval: The MCP Server securely forwards structured requests from the MCP client to VERA’s REST API endpoints. For instance, this might involve an HTTPS call such as GET /product-passports/12345 with specific filters (e.g., retrieving the carbonFootprint field). All data retrieval occurs exclusively through these defined API endpoints — no direct database queries or SQL access are permitted, maintaining rigorous data security. VERA’s data is often represented as digitally signed JSON documents (verifiable credentials). Currently, signature verification is handled on the client side: MCP clients can implement this verification logic as needed to ensure data authenticity and integrity, particularly for sensitive or compliance-related operations. In future platform iterations, Spherity’s planned end-to-end Agent Infrastructure will include integrated support for automated signature verification to further enhance security and trust. If requested data is distributed (e.g., stored both off-chain and via on-chain references), the MCP Server transparently retrieves and aggregates it via API calls, returning a unified dataset to the MCP client (such as carbonFootprint: 50 kg CO₂, along with relevant metadata like confidence scores or source references).
   

5. Data Post-Processing & Privacy Filtering: Once the data is retrieved from VERA’s API, the MCP Server returns it directly to the requesting MCP client without performing additional transformations or selective disclosure processing. Spherity’s privacy-focused design ensures sensitive data (such as personal or confidential supplier information) is stored in separate credentials or derived credentials, adhering to the W3C Verifiable Credential Data Model and, in the future, employing advanced cryptographic methods (e.g., Data Integrity BBS Cryptosuites v1.0 and zero-knowledge proofs). Currently, privacy enforcement — including selective disclosure — is handled directly within VERA’s API layer. The API ensures that sensitive data is only included in responses when the requester is explicitly authorized. Thus, the MCP Server itself does not perform privacy filtering or data masking; it relies on VERA’s existing API to enforce access controls and data privacy policies.
   

6. Response Construction: The MCP Server returns the retrieved data directly to the requesting MCP client in JSON format, exactly as provided by the underlying VERA API. No additional interpretation, formatting, or data processing is performed by the MCP Server itself. It is the responsibility of the client-side AI (LLM) to interpret this JSON data, construct user-friendly answers, and present them appropriately. For example, the MCP Server returns structured data such as:

The client AI then utilizes this structured response to formulate a clear and contextually relevant reply for end-users, potentially including source attribution or credential references.

7. Return to AI Client: Finally, the MCP Server sends this response back to the AI client. The AI model incorporates the data into its answer to the user’s question, or uses it in whatever task context required. Importantly, the model’s context window now has fresh, verified data from the DPP, which improves the relevance and accuracy of its output.

Throughout this process, authentication and authorization are paramount. Spherity leverages a combination of modern Auth mechanisms and decentralized identity for this. The MCP server itself is a secure service — typically, the AI application must authenticate to the MCP server (e.g. using an API key or OAuth token associated with a particular role). Within VERA, enterprise wallet credentials and security groups define what data an entity can access. For example, a regulator’s AI agent might have a credential proving it is a “Regulator — Market Surveillance” PLI (Person of Legitimate Interest); the VERA API validates this credential and then allow queries of compliance data that regular users cannot see. Spherity’s system uses role-based access control and verified claims to ensure only authorized queries go through. In practice, this means if an unauthorized AI agent tried to query confidential data (say, detailed BOM of a competitor’s product), our VERA solutuion would deny the request or omit those fields.

Data Privacy & Security: The integration of MCP does not override VERA’s strong security posture; instead, it extends it to AI interactions. All data transactions via MCP are logged and can be audited, just like regular API calls. The MCP protocol itself emphasizes secure, two-way communication, often over TLS, with minimal retention of data on the AI side beyond the session. Spherity likely deploys the MCP server within a controlled environment and may utilize sandboxes or isolation to ensure an AI agent cannot perform actions outside its scope (this prevents scenarios where an AI could, say, attempt to inject malicious queries — the MCP server will only execute well-formed, allowed queries). Recent security analyses have noted the importance of properly configuring MCP servers to avoid unauthorized control; Spherity addresses this by requiring authentication on all endpoints and by whitelisting the types of queries that can be executed (e.g. read-only queries for most AI uses, with no direct write/delete unless explicitly permitted in a use case).

Furthermore, since VERA deals with verifiable credentials, data provenance and integrity are built-in. When an AI retrieves data via the MCP server, it is essentially pulling digitally signed facts from the DPP (e.g. the manufacturer’s signature on the “CO₂ footprint” claim). This means the AI’s responses can be backed by verifiable evidence. In technical terms, the MCP server or AI client could verify the credential’s signature using Spherity’s trust chain before the AI uses it. This ensures the AI isn’t unknowingly using tampered data. In user-facing AI assistant scenarios, the assistant might even present a “verified” badge or cite the DPP source, which increases trust in AI outputs.

Workflows and Integration: A practical example of the MCP-VERA workflow could be a chatbot interface for a Digital Passport Helpdesk. A manufacturer implements an AI assistant for field technicians. A technician can ask, “What are the dismantling steps for battery pack SN XYZ?” The AI (via MCP) queries VERA for that battery’s passport, specifically the “Responsible End-of-Life” section where dismantling instructions are stored (perhaps as a PDF or text). The MCP server fetches the instructions (ensuring the technician is authorized to view them via their credentials), and the AI then answers with step-by-step guidance, even quoting the official instructions and perhaps offering to open the full document. This workflow involves multi-step data gathering and highlights how APIs and AI together improve usability — the alternative would have been the technician manually searching through a database or physical manual.

From a system architecture diagram perspective, one can visualize the MCP Server as an additional layer on the standard VERA architecture: external AI apps connect to the MCP interface, which in turn communicates with VERA’s microservices and databases behind the scenes. The MCP Server ensures conversational latency is minimized (by intelligently caching context, etc., so that AI responses come quickly). Spherity likely has designed this component to scale horizontally, as enterprise AI queries may be frequent and time-sensitive.

Integrating the MCP Server with VERA’s DPP system adds a governed, intelligent gateway for AI. It preserves VERA’s robust security (through context-based auth and data filtering) while allowing seamless data flow to and from AI models in real time. This architecture means clients can confidently deploy AI solutions — like compliance monitors, customer chatbots, or predictive analytic engines — that interact with digital product passports without compromising on data integrity or confidentiality. As a result, VERA’s rich DPP data can be operationalized by AI in a safe, standardized manner, truly making the system “AI-ready.”

5. Generative AI Use Cases Enabled by AI-Ready DPPs

With MCP server integration into Spherity’s DPP solution, generative AI enables new insights, automation, and user interactions, extending far beyond static data applications. Key AI-enabled use cases and stakeholder benefits include:

Data Verification & Validation:Generative AI automates passport data auditing, flagging inconsistencies or missing certificates. For example, it might detect anomalies in declared carbon footprints or incomplete documentation.

• Manufacturers & Supply Chain: Early detection of compliance risks, reducing audit issues.

• Consumers: Trust increased via verified claims and accuracy.

• Regulators: Efficient oversight through AI-generated anomaly reports.

• Retailers: Nightly checks to prevent non-compliant products from entering sales channels.

• Recycling Actors: Reliable data to ensure accurate recycling and reporting.

Intelligent User Interfaces (AI Assistants):AI assistants using DPP data via MCP answer natural language queries. Consumers or workers can directly interact with product data without manual searching.

• Manufacturers & Supply Chain: Instant internal data access for compliance checks.

• Consumers: Enhanced engagement, personalized information about product sustainability and recycling.

• Retailers: AI-driven product assistants integrated in-store or online to enhance customer experiences.

• Regulators: Chatbots providing regulatory guidance using official DPP data.

• Recyclers: Voice-assisted guidance for safe product dismantling or recycling instructions.

Predictive Analytics for Lifecycle & Compliance:AI leverages DPP data for predictive maintenance, compliance forecasting, and product lifecycle management.

• Manufacturers: Identify early failure patterns, prompting preventive design improvements.

• Supply Chain Actors: Forecast shipment risks based on product attributes logged in DPP.

• Consumers: Receive predictive maintenance notifications, ensuring continuous product use.

• Regulators: Anticipate compliance trends and adjust policy proactively.

• Retailers: Manage inventory based on predictive insights, proactively handling warranty issues.

• Recyclers: Forecast material recovery flows, enhancing recycling efficiency and planning.

Dynamic Monitoring of Regulatory & Environmental KPIs:AI provides real-time KPI monitoring based on aggregated DPP data, moving beyond static reporting.

• Manufacturers: Automated alerts and periodic sustainability performance summaries.

• Regulators: Real-time insights on circular economy metrics and supply chain vulnerabilities.

• Retailers: Sustainability scoring for stocked products, ensuring compliance.

• Recycling Networks: Real-time recycling rate calculations, identifying areas needing improvement.

Macro-Level Insights for Authorities:AI supports strategic analysis and scenario planning by synthesizing aggregated DPP data.

• Policy Makers: Model scenarios like the impact of increased recycling rates on critical material imports.

• Industry Associations: Analyze sector-wide trends, enabling informed regulatory dialogues.

• Sustainability Researchers: Rapidly access macro-level data for comprehensive environmental studies.

Integrating generative AI transforms DPPs from static documentation tools into dynamic, interactive systems. AI ensures verified data quality, real-time actionable insights, and connects micro-level product data to macro-level sustainability improvements, amplifying the strategic value of Digital Product Passports.

6. Case Studies: AI-Enabled DPPs in Action

To illustrate the concepts discussed, we present three case studies (drawn from real pilots or realistic scenarios) showing how Spherity’s AI-enhanced Digital Product Passports deliver value in different sectors: automotive batteries, stationary batteries, and textiles. Each case study outlines the context and stakeholders, the integration of the MCP/GenAI features, and the outcomes achieved.

Case Study 1: EV Battery Passport for Fleet Management (Automotive Batteries)

Context & Actors: A major commercial vehicle manufacturer (OEM) partnered with Spherity to deploy digital passports for its electric truck and bus batteries. The fleet consists of heavy-duty trucks whose battery packs (each ~300 kWh) are a critical asset. Stakeholders include the OEM’s production team (issuing the DPPs at battery assembly), fleet operators (the OEM’s clients who manage day-to-day truck operations), service centers, recyclers, and regulators monitoring battery compliance. The goal was twofold: ensure compliance with the EU Battery Regulation early (future-proofing for 2027) and optimize the batteries’ lifecycle value (since these expensive batteries can have second-life uses).

MCP & GenAI Integration: Each battery was equipped with IoT sensors (via the Battery Management System, BMS) feeding data into its VERA digital passport in real-time. Using the MCP server, this data became accessible to AI systems. The OEM deployed an AI-powered Battery Lifecycle Management Assistant — essentially a dashboard with an AI chatbot and analytics engine tuned to the battery DPPs. Through MCP, the AI could query any battery’s status, history, and prognostics from its DPP. For example, if a fleet manager typed “How is Battery #SN ABC123 performing?”, the AI would retrieve the latest metrics: state-of-health 92%, temperature within norms, 1,200 charge cycles, etc., and generate a natural language reply with trend insights. The AI was also configured for predictive maintenance: it analyzed the streaming data in the passports (charging patterns, temperatures, etc.) and predicted maintenance needs. In one instance, the AI warned that a subset of batteries showed higher internal resistance (indicator of aging) and recommended scheduling those trucks for service within 2 weeks — preventing on-road failures. Additionally, the MCP integration allowed the AI assistant to automate compliance reporting. When new EU battery recycling rules came into effect, the fleet manager simply asked, “Do all our battery passports meet the new EU data requirements?” The AI cross-checked each DPP for the required fields (e.g. carbon footprint data, dismantling instructions) and responded that 98% were compliant, flagging two passports that missed a recently added field. This prompt identification let the OEM fix those passports quickly, ensuring full compliance well before regulatory audits.

Outcomes & Stakeholder Value: This project yielded significant benefits:

• For the OEM (manufacturer): They now have a dynamic, trustworthy record of each battery’s life. The DPPs, secured with verifiable credentials, mean any claims about the battery (performance, safety, etc.) can be proven to third parties. Internally, the AI-driven insights led to design improvements: the AI noticed that batteries used in very hot climates degraded faster, prompting the OEM to enhance cooling systems in the next design iteration. Moreover, the OEM can confidently demonstrate compliance and innovation to regulators and customers, using this as a selling point (indeed, it positions them as an early adopter, ahead of the 2027 legal mandate).

• For Fleet Operators: The fleet companies managing these electric trucks saw reduced downtime and cost. The AI assistant proactively scheduled maintenance only when needed, avoiding both catastrophic failures and unnecessary routine checks. One fleet reported a 15% extension in average battery life thanks to optimized charging practices recommended by the AI (e.g. the AI advised adjusting charging cycles for overnight depot charging based on each battery’s health data). The DPP-based chatbot also simplified training for their technicians — a new hire could ask the assistant questions about the battery (“What does error code XYZ mean?”) and get answers drawn from the manufacturer’s data in the passport. This saved time and ensured consistent, accurate information.

• For Recyclers & Second-Life Users: When these truck batteries reached end-of-first-life (e.g. 8–10 years or at ~70–80% capacity), the digital passports became invaluable. The OEM’s passport data allowed a second-life battery company to easily identify which used batteries were good candidates for repurposing as stationary storage. In the case study, a renewable energy firm consulted the DPPs (with permission) via an AI query: “List all batteries from Fleet X that will have >70% capacity by 2030 and their locations.” The AI aggregated data from dozens of passports and output a list of 50 batteries suitable for a 20 MWh solar farm storage project. Each passport’s verified history (usage patterns, no major incidents, performance Category A) gave confidence that these batteries could be safely reused. For batteries not suited to second-life, recyclers accessed the passports to get dismantling instructions and composition data. One recycler noted that having the step-by-step disassembly guide (pulled by an AI voice assistant in the workshop) reduced the time to break down a battery by 30% and improved safety (workers knew exactly where disconnects were, as confirmed by the DPP). Regulators in turn were happy to see that each recycled battery’s passport was updated with a recycling certificate (using Spherity’s system to issue a VC when materials were recovered), enabling end-to-end traceability.

• For Regulators: Although behind the scenes in this case, authorities benefited from the pilot’s transparency. During an audit, the OEM provided the verifiable DPP data instead of hundreds of PDFs — an AI tool on the regulator’s side quickly verified digital signatures and checked key compliance metrics (like confirming all batteries had a verified carbon footprint entry). This greatly streamlined the audit, showcasing how DPPs plus AI can reduce administrative burdens for compliance. In fact, the regulator called this project a “gold standard” example of battery passport implementation, informing upcoming guidelines.

  
  

Overall, this case demonstrates how AI-enhanced DPPs optimize the entire lifecycle of EV batteries: real-time monitoring, efficient use, regulatory compliance, and smooth end-of-life transition to recycling or second use — delivering economic and environmental wins. Explore our BVG Electric Bus Case Study and a simple DBP Example.

Digital Battery Passports in action: Each battery in this BVG electric bus is equipped with a QR code linking to its verifiable digital passport and dynamic battery health acquisition on a daily base— supporting safety, service, and circularity. ©Battery & QR-Code: Michael Wagner/BVG

Case Study 2: Smart UPS Product Passport for Sustainable Facilities (Stationary Batteries)

Context & Actors: Schneider Electric, a global energy solutions provider, undertook a pilot with Spherity to create a Digital Product Passport for its Galaxy VL UPS systems (large Uninterruptible Power Supply units used in data centers and hospitals). These UPS units contain sizeable battery banks and electronics to ensure power backup. The main actors are Schneider Electric’s product compliance team, its sustainability division, enterprise customers who buy the UPS, maintenance service partners, and auditors verifying compliance (both internal and external). Schneider’s objectives were to showcase transparency and sustainability leadership in a traditionally opaque industry (power infrastructure) and to simplify life-cycle services for their customers through digital means.

Schneider Electric Galaxy UPS Systems Product Passport, powered by Spherity’s DPP technology, highlights the essential technical and environmental attributes of the Galaxy VL series. Soource: Public DPP Demo.

MCP & GenAI Integration: The Galaxy UPS Passport was created in VERA with comprehensive data: manufacturing details (plant in France, Jan 2023), technical specs (kW ratings, supported battery types), and sustainability metrics (like a Greenhouse Gas Performance Category A rating, and a cradle-to-gate carbon footprint of 200 kg CO₂e for the unit). It also included due diligence scores (Child Labor: 86, Human Rights: 88) derived from supplier audits by RCS Global. Once the passport was in place, Schneider integrated an AI-powered customer portal on top of it. Through MCP, the AI portal could answer customer queries and provide insights by accessing the passport data.

For instance, a facility manager who purchased this UPS logs into the portal and asks, “Show me how this UPS contributes to our sustainability goals.” The AI (using the MCP server) pulls the UPS’s DPP data: it finds the carbon footprint figure, notes that the unit has an Optimized Ecofit Service plan (which extends life), and that its design is 90% recyclable. The AI then generates a friendly report: “Your Schneider Galaxy UPS is rated Category A for greenhouse gas performance, with a verified manufacturing carbon footprint of 200 kg CO₂e. It supports an Ecofit service program, meaning its batteries can be replaced and recycled to extend lifespan. 88% of its components are recyclable at end-of-life. Using this UPS aligns with your facility’s ISO 14001 objectives by reducing downtime and avoiding the carbon impact of power outages.” This personalized summary helps the customer communicate the UPS’s sustainability value to their stakeholders.

Another use of the AI portal is interactive troubleshooting and maintenance. The UPS has a digital twin in the DPP that logs operational status. If an alarm goes off on the UPS, the facility engineer can type, “What does Alarm Code 0xZ37 mean and what should we do?” The AI references the passport’s “Optimized Use — Ecofit Service Book” section where such information is stored. It finds that 0xZ37 corresponds to a battery module fault. The AI responds: “Alarm 0xZ37 indicates a battery module discrepancy. According to the product passport, the recommended action is to run a battery self-test and contact service if the error persists. I can see from the passport data that Module #3 was last replaced 4 years ago. It may be nearing end-of-life. I advise scheduling a preventive replacement.” Impressively, the AI also offers to initiate the service process: “Shall I create a service ticket with Schneider Electric for a battery module check? I have the unit’s serial and warranty info from its passport.” The engineer says yes, and the AI, through an integration, raises a ticket with all relevant details (device ID, location, issue) auto-filled — no paperwork needed on the engineer’s part.

Outcomes & Stakeholder Value:

• For Schneider Electric: The DPP pilot served as a powerful marketing and differentiation tool. They publicly demonstrated the world’s first UPS with a verifiable digital passport, positioning them as forward-thinking and reliable. As evidence, the passport was showcased at a trade fair where prospective clients could scan a QR code on the UPS and see the rich data (including sustainability scores) on a screen. Many data center customers expressed that this level of transparency gave them greater confidence in the product’s quality and Schneider’s accountability. Internally, Schneider’s teams benefited too: the passport’s data enabled easier compliance with new EU rules (like the EU Battery Regulation for the UPS’s batteries, and ESPR for electronics). One Schneider compliance manager noted that instead of assembling dozens of documents for a CE audit, they could just present the digital passport which “highlights the essential technical and environmental attributes” of the UPS in one place. The AI integration also reduced support costs — routine questions that would have gone to Schneider’s call center (like interpreting alarms or requesting service) were now handled by the AI portal, 24/7, with high accuracy, since it was drawing from the official product data.
  

• For Enterprise Customers (Facility Managers): They gained a single source of truth and an intelligent assistant for their power system. This simplified their operations significantly. Instead of flipping through a thick user manual, they could just ask the AI. It saved time and prevented errors; for example, if a manager was unsure about compliance (say, “Does this UPS meet the new EU battery labeling requirement?”), the AI could confirm it by citing the DPP’s compliance section. The sustainability insights helped them report progress to their bosses — e.g., incorporating the UPS’s footprint and circular design info into the company’s sustainability report to show how they invest in greener infrastructure. The predictive maintenance aspect reduced downtime: in one incident, the AI detected from passport data that the battery capacity was gradually decreasing and alerted the facility team two months before a potential failure. A planned replacement was done without any outage, as opposed to a chaotic emergency swap during a power failure.
  

• For Service Partners: Third-party service companies maintaining Schneider equipment also got controlled access to the DPPs. Instead of maintaining their own records (which might be incomplete), they could query the passport for last service dates, parts replaced, etc. When on-site, a technician could use a tablet to interact with the AI assistant: “Show maintenance history for UPS #123” — the AI would list all past interventions (e.g. “Battery modules replaced on 2021–09–10, firmware updated on 2022–03–05”) along with any outstanding service bulletins. This improved service quality and speed. It also ensured any updates they made were written back to the DPP (issuing a verifiable credential for the maintenance action), keeping Schneider and the customer in the loop instantly.
  

• For Regulators/Auditors: Although not directly interacting with AI in this case, the outcome was a system that inherently made compliance transparent. A certification body auditing the UPS for safety and environmental compliance could access the DPP (with permission) and see all relevant documents (like the EU Declaration of Conformity, which in the passport was indicated as “Yes” for having one, plus could link to the actual document). The AI could also be used by Schneider’s internal audit to query, “Do any deployed UPS units lack an end-of-life plan in their passport?” ensuring they meet obligations under extended producer responsibility. The answer was provided within seconds, showing all units indeed had end-of-life info (since the passport has a “Compliance Navigator” section addressing such frameworks). This kind of proactive compliance monitoring impressed auditors and potentially reduces the frequency or scope of external audits needed.

The Galaxy UPS case shows how AI-enabled DPPs improve both the customer experience and the sustainability profile of industrial products. By integrating technical, compliance, and lifecycle data into one digital ledger and layering AI on top, Schneider and its clients realized smoother operations, better accountability, and a strong narrative for sustainability. It’s a template that Schneider is looking to expand to other product lines (e.g. large transformers, switchgear), and it provides a global relevance example: any complex equipment — be it medical devices, industrial machines, or building systems — can benefit from this approach of a digital passport plus AI assistant.

Case Study 3: Circular Fashion Passport Pilot with AI Coach (Textiles)

Context & Actors: A mid-sized fashion brand in Italy, EcoWear, engaged Spherity in a pilot to implement Digital Product Passports for their new sustainable clothing line (including organic cotton T-shirts and recycled polyester jackets). This was driven by forthcoming EU requirements for textile passports (expected around 2026–2027) and the brand’s desire to strengthen its eco-friendly image. Actors in this case include EcoWear’s product development team, its marketing department, retail store staff, end consumers, and a recycling partner that works with the brand’s garment take-back program. Additionally, the pilot was showcased at Sicily Fashion Week 2025, involving industry observers and EU policymakers interested in textile traceability.

From sail to stylish: This upcycled ‘sports bag’ by Junkle comes with a Digital Product Passport, making its circular story traceable and transparent — just scan the QR code to learn more. Source: Spherity GmbH.

MCP & GenAI Integration: Each garment in the collection was given a VERA digital passport with a DID, and a NFC/QR code was attached to the clothing tag. The passport contained details like material composition (e.g. “100% GOTS-certified organic cotton” for the T-shirts, or “50% recycled PET, 50% virgin polyester” for the jackets), the factory of manufacture (with a verified fair labor certification), care instructions, and end-of-life info (e.g. this item is part of a return-for-recycling program). EcoWear then integrated an AI-powered “Smart Wardrobe Assistant” for consumers, accessible via a mobile app or by scanning the QR code on the clothing tag.

When a customer scanned the code in-store, the AI assistant would greet them: “Hi! I’m EcoWear’s smart assistant. I can tell you all about this item.” The customer could ask natural language questions. For example:

• “Where was this shirt made?” — The AI, via MCP, fetched the passport’s data: made in Portugal, at a specific certified factory. It answered: “This T-shirt was ethically made in Guimarães, Portugal, in a solar-powered facility that pays fair wages.”
  

• “What’s it made of?” — The AI saw 100% organic cotton in the DPP and responded: “It’s crafted from 100% organic cotton, certified by GOTS, meaning no harmful chemicals and reduced water use in farming.” It might even pull a stat from the DPP such as carbon footprint if available, e.g. “Its production saved about 20% CO₂ compared to a conventional cotton tee.”
  

• “How do I wash it to be sustainable?” — The AI used both the care instructions and some generative capability: “The passport recommends washing at 30°C (cold wash) and line drying. This not only protects the fabric but also saves energy — a win for sustainability!”
  

At Sicily Fashion Week, EcoWear set up an interactive booth: attendees could pick up a garment and talk to the AI assistant via a display. The MCP integration ensured that all answers were grounded in the actual product data, making the experience credible (no generic greenwashing). The AI also had a bit of personality tuned to EcoWear’s brand — encouraging users to engage: “Feel the fabric — that softness is organic cotton with no toxic dyes. Pretty cool, right?”

After purchase, the AI assistant remained useful. Consumers at home could scan their garment to access a “digital wardrobe”. The AI might send friendly notifications: “Hey! It’s been 6 months — if your EcoWear jacket ever needs repair, remember you have free minor repairs for 2 years. I can show you how to sew a button too!” If the user asks, “Can I recycle this when it’s worn out?”, the AI cites the DPP’s end-of-life section: “Yes. EcoWear has a take-back program. You can bring it to any EcoWear store or mail it in, and we’ll recycle it into new fabric. In fact, 75% of this jacket’s material can be recycled. Your digital passport will update once it’s recycled, so you’ll know it contributed to a new product!”

EcoWear T-Shirt with an integrated Digital Product Passport powered by Spherity’s VERA solution — scan to explore transparent sustainability data, material origins, and care instructions. Source: Spherity VERA Product Page.

Outcomes & Stakeholder Value:

• For EcoWear (Brand): The pilot was a hit in terms of customer engagement and brand differentiation. Shoppers spent more time interacting with products (store staff observed that people loved asking the AI questions, often leading to more appreciation of the product’s value). This translated into a measurable uplift in sales for the sustainable line — customers stated they were willing to pay a bit more because the DPP and AI proved the items’ quality and ethical sourcing (trust was built). EcoWear’s marketing team leveraged insights from the AI interactions: they saw, for example, many consumers asked about recycling and material impact. This feedback helped them tailor future communication and product design (they realized customers highly value recyclability, so they’re exploring mono-material designs for easier recycling). On the compliance side, EcoWear feels prepared for the 2027 textile DPP mandate; they have experience with the data collection and can show policymakers a working model. Indeed, EU officials at the fashion week praised the initiative, noting that “a digital product passport for textiles, combined with user-friendly AI, can truly educate consumers and increase textile circularity”. This positions EcoWear favorably in potential public-private pilots or grant programs.
  

• For Consumers: They received rich information and support that enhanced their ownership experience. Rather than vague claims on a swing tag, they got detailed, verified info on origin and impact, which many found empowering. It gave them assurance that the premium they might pay for sustainable fashion is going to the right cause (since the passport proved, for example, organic content and fair labor). Post-purchase, the AI assistant helped them care for the garment sustainably (e.g. wash and repair guidance) which can prolong the item’s life — consumers benefit by getting more use out of what they bought. And when they’re done with the item, the DPP integration makes returning it easy (the app could generate a return QR code referencing the item’s DID, etc.). Some pilot users reported that the process of scanning and interacting with the garment’s passport made them more attached to the product — knowing its story created an emotional connection, potentially reducing the likelihood of treating it as disposable fast fashion. It’s early data, but EcoWear’s survey found customers who used the digital passport were 20% more likely to say they will keep the garment for a long time (versus a control group). This hints at a positive behavioral shift toward sustainable consumption.
  

• For Recycling/Second-hand Partners: The recycling partner found the passports extremely useful in sorting and processing returns. Instead of relying on clothing labels (which can be missing or faded), workers could scan the item’s QR and instantly know the material composition. One scenario: EcoWear had a partnership with a second-hand platform; items that customers returned for recycling that were still in good condition could be diverted to resale. The DPP and AI helped here: an AI agent (with proper access) evaluated returned items by checking their use history (the passport could log if the item was worn heavily or if it had repairs). Combined with a physical check, this triaged whether an item should go to second-hand or straight to recycling. The result was that a few garments got a second life through resale, and those that didn’t were recycled with clear material identification (e.g., all-cotton shirts went to a cotton recycler). The AI also generated a sustainability report for EcoWear after 6 months: it summarized how many garments had been returned and recycled, how many were resold, and the estimated material recovered. For instance, “100 EcoWear jackets were returned, 30 were resold (saving X kg CO₂ by displacing new production), 70 were recycled yielding 35 kg of recycled polyester fiber,” etc. This data, previously very hard to compile, was now readily available through the DPP system and AI analysis — a big plus for EcoWear’s sustainability tracking.
  

• For Retail Staff: Initially, store employees were wary that the AI kiosk might replace some of their roles. In practice, it became a helpful co-worker that handled detailed sustainability questions, while staff could focus on styling or checkout. Staff actually learned from the AI too — by hearing the AI’s answers, they became more fluent in the product’s sustainable features. This made the whole store more knowledgeable. One staff member recounted a scenario where a customer, after chatting with the AI, still had a couple of questions; the staff could confidently continue the conversation, reinforcing what the AI said and adding a personal touch. This augmented the staff’s capacity to engage customers meaningfully, rather than reducing their role.

  
  

The EcoWear case study exemplifies how AI-enabled DPPs can transform the fashion industry by bridging the information gap between producer and consumer. It shows that when consumers are given verified info in an interactive way, they respond with greater trust and engagement. For the brand and broader industry, it underscores the potential to increase circular practices (like repair and recycling) through convenient digital tools. It’s a model that can be globally replicated — imagine every clothing item having a scannable passport and AI guide; it could drastically reduce misinformation (like false “organic” claims), improve care habits, and boost recycling rates (tackling the huge textile waste problem). As one EU Parliament report noted, a digital passport in textiles can “enhance traceability, circularity, and transparency”, and EcoWear’s pilot brought that vision to life on the ground, with the added magic of AI to engage and educate stakeholders at every step.

7. Conclusion & Call to Action: Partner with Spherity for AI-Enabled DPP Innovation

The above exploration — from introducing Spherity’s GenAI-ready VERA platform and the regulatory drivers, through detailed use cases and real-world pilots — demonstrates that Digital Product Passports augmented with AI are not a far-off concept, but a present reality and a strategic imperative. They are enabling unprecedented levels of transparency, efficiency, and sustainability across product lifecycles. Businesses that embrace this innovation early will not only navigate upcoming regulations with ease but also unlock new value propositions, operational savings, and trust with customers and partners.

Spherity’s VERA DPP solution with MCP integration stands at the forefront of this transformation. It provides a robust, scalable infrastructure to digitize your product information into secure passports, and now — with the Model Context Protocol — it makes that information readily accessible and actionable through AI. This combination turns static data into dynamic insights and services. Whether it’s an AI assistant helping your customers make informed choices, or an internal analytics bot optimizing your supply chain, the possibilities are vast.

For businesses and institutions, the time to act is now. The EU’s regulatory timeline is ticking — major requirements kick in starting 2024 and will expand quickly to cover more products. Moreover, consumer and market expectations for transparency and sustainability are rising globally. By partnering with Spherity, you can move from compliance-as-a-cost to compliance-as-an-opportunity — leveraging DPPs and AI to drive innovation, differentiation, and growth.

Next Steps / How to Get Started:

1. Reach Out for a Demo or Consultation: Spherity’s team is ready to demonstrate the VERA platform and discuss how it can be tailored to your specific industry and products. (For instance, if you are an electronics manufacturer, we can show how a prototype DPP for one of your products would look and function, including integration of AI queries.).
   

2. Pilot a Use Case: Identify a pilot scope — perhaps a particular product line or a supply chain process — where you can implement a Digital Product Passport and test AI integration. Spherity often recommends a small-scale pilot (3–6 months) where we help you digitize the required data, issue passports (using our VERA Studio tools for rapid prototyping), and set up an AI application (like a chatbot or dashboard) for a selected use case. This pilot will yield insights and tangible results to build a business case.
   

3. Collaborate on Data and Integration: Successful DPP projects involve the ecosystem — your suppliers, IT systems, and possibly customers. Spherity will work with your team to integrate VERA with your existing data sources (e.g. PLM or ERP systems to ingest BOM data, certification databases for compliance docs) and set up the MCP server in your environment or cloud. We ensure that authentication, privacy, and data ownership aspects align with your corporate policies, while still enabling seamless data flow to AI in a governed way.
   

4. Scale Up Deployment: After a pilot proves the concept, Spherity supports scaling to full production. VERA is enterprise-ready — capable of handling millions of passports — and can be rolled out across product categories and geographies. We also provide training and change management support, because adopting DPPs often means new processes (e.g. educating your suppliers to provide data that goes into the passport). With the pilot’s ROI data in hand (for example, saved labor hours in audits, increased sales due to consumer trust, etc.), you can confidently invest in broad deployment.
   

5. Engage in the DPP Ecosystem: By partnering with Spherity, you also join a network of innovators and standard-setters. We encourage clients to actively engage in standardization initiatives and industry consortia (like Battery Pass, CIRPASS, W3C working groups) to stay ahead and help shape the frameworks. Spherity is at the table in many of these discussions, and we’ll ensure your interests and insights are voiced. This also means you’ll be well-informed of upcoming changes (e.g. new delegated acts) and technical standards, so you remain compliant and compatible.
   

Call to Action: The convergence of regulatory pressure, consumer demand, and technological maturity has created a pivotal moment. Digital Product Passports are becoming the norm — and with generative AI, they are becoming powerful business tools. We invite manufacturers, brands, retailers, and institutions to collaborate with Spherity in pioneering this new landscape. Whether your focus is on compliance (meeting EU rules), on sustainability (achieving circular economy goals), or on innovation (creating smart products that communicate), an AI-enabled DPP can be the key infrastructure to achieve it.

Take the step to future-proof your business. Contact Spherity today to schedule a demonstration or strategy workshop. Together, let’s build a pilot that showcases what AI-enhanced digital product passports can do for you — be it reducing your carbon footprint reporting effort by 50%, boosting customer loyalty through transparency, or cutting recall costs with real-time monitoring.

As seen in our case studies, the technology is ready and delivering results. Spherity’s VERA platform provides the secure backbone, and our new MCP/AI integration opens up endless possibilities for automation and insight. By partnering with us, you’ll be joining other forward-thinking organizations in turning regulatory compliance into competitive advantage. In the words of an automotive sustainability manager reflecting on digital product passports, “with the DPP, we have the chance to look at where all these materials are going… DPP is absolutely necessary for business resilience and for the planet.”.

Your next step: Embrace that chance. Let’s collaborate to make your products not only compliant or smart, but truly intelligent, transparent, and circular by design. Spherity is here to guide you on this journey — from the first verifiable credential in your product’s passport to the first question your custom AI assistant answers for a delighted customer. The future of product ecosystems is here; come be a leader in it.

Contact Spherity — and let’s co-create the future of Digital Product Passports, today.