PIM and product content
Product attributes, images, taxonomy, translations, merchandising rules, and pricing context become governed catalog intelligence.
Regulated Retail Agentic OS Control Plane
Retail AI agents that turn commerce objectives into governed omnichannel execution
VDF.AI sits above PIM, OMS, POS, ecommerce, CRM/CDP, inventory, consent, and service systems. State the retail objective and the OS activates the right agents, tools, brand gates, and audit trail while keeping customer data, card context, and margin strategy inside your boundary.
6Retail workflows across service, content, search, inventory & stores
0PIM, OMS, POS, CRM or contact-center migrations required
100%On-premise or sovereign cloud for customer data
Every runConsent checked, brand reviewed and audit logged
Built for customer trust
GDPR EU AI Act PCI DSS ePrivacy PSD2 ISO 27001
Retail control plane
Customer and commerce intelligence in. Governed control plane. Omnichannel execution out.
VDF.AI sits above PIM, OMS, POS, ecommerce, CRM/CDP, contact center, inventory, returns, consent, and policy systems. It coordinates retail agents without pushing customer data, card context, or margin strategy into third-party AI.
01 Intelligence in 02 Control plane 03 Agents and tools 04 Execution out
Intelligence in
OMS, POS and ecommerce events
Orders, returns, delivery status, basket context, and store events feed service and allocation workflows.
CRM, CDP and service history
Profiles, preferences, consent, complaints, and service records are retrieved only within role and purpose limits.
Inventory, returns and demand signals
Sell-through, stockouts, return reasons, promotions, and regional demand patterns support planning decisions.
Consent, brand and compliance rules
Privacy rules, PCI boundaries, promotion policy, and approved language shape what each agent can say or do.
Live governed execution
VDF AI - Retail - Model agnostic - Sovereign cloud - Any LLM
Regulated Retail Agentic OS Control Plane
Objective engine, consent controls, brand guardrails, agent registry, memory, and feedback across service, content, inventory, and personalization.
Retail objective engine
State the target: reduce contact volume, improve search, localize content, recover margin, or retain more customers.
Consent, PCI and brand gates
Controls enforce customer permissions, card-data boundaries, brand tone, channel policy, and reviewer requirements.
Orchestration
Commerce agent router
Ranks actions by customer intent, channel, margin impact, stock position, privacy rule, and approval threshold.
Omnichannel service pod
Answers product, policy, delivery, and return questions with full account context and channel history.
Content and enrichment pod
Generates, localizes, and normalizes product copy and attributes for review before publishing.
Demand and inventory pod
Summarizes inventory risk, demand swings, return signals, and allocation options for planners.
Personalization pod
Coordinates recommendations, audiences, and message variants under consent, fairness, and brand limits.
Sovereign customer-data fabric
Runs on-premise or private cloud so customer profiles, order history, and campaign data stay inside your perimeter.
Retail memory and feedback loop
Resolved contacts, product gaps, stock risks, and approved content variants become reusable institutional knowledge.
Execution out
Customers answered
Service responses are grounded in current order, product, policy, and consent context.
Content published
Descriptions, attributes, translations, and promotion copy move through brand review faster.
Search enriched
Catalog tags, synonyms, and attribute gaps are cleaned so discovery improves.
Inventory briefed
Demand, return, and stock signals become concise planner briefs with evidence.
Personalization approved
Recommendations and journeys respect consent, channel policy, and reviewer thresholds.
Associates enabled
Store teams get consistent product, promotion, and policy answers inside approved knowledge boundaries.
From objective to outcome
How regulated retail operations transform
The control plane turns channel goals into governed agent execution across service, merchandising, store operations, inventory, and personalization.
- 1
Your commerce stack stays
PIM, OMS, POS, ecommerce, CRM, CDP, contact-center, inventory, and consent systems stay where they are. VDF.AI coordinates above them.
No platform migration - 2
The retail objective drives the work
Reduce handling time, enrich catalog search, localize content, improve allocation, or personalize under consent. The OS returns a plan by channel, data class, and approval path.
Goal-led orchestration - 3
Agents execute within customer trust boundaries
Service, content, inventory, personalization, and associate agents operate with GDPR, PCI, consent, brand, and channel policies in force.
Controlled autonomy - 4
The OS learns from outcomes
Resolved contacts, failed searches, inventory risks, and approved content become reusable memory for future runs.
Measurable feedback
The Industry Challenge
The AI dilemma in regulated retail & omnichannel
Retailers hold rich data on millions of customers and the content needs of enormous catalogues. AI can personalise, serve, and merchandise at scale — but customer PII and payment context can't be poured into a hosted model without serious GDPR and PCI exposure.
01
Customer-Data Exposure
Profiles, order history, and behaviour are GDPR personal data at massive scale. Sending it to a hosted LLM is a DPO's nightmare.
02
PCI & Payment Scope
Anything touching payment context risks expanding PCI DSS scope. AI tooling must stay well clear of cardholder data paths.
03
Content at Catalogue Scale
Product descriptions, attributes, and localised content for huge, fast-changing catalogues outpace what manual teams can produce.
04
Peak-Season Economics
Demand spikes hard at peak. AI must scale cost-effectively across millions of interactions, not blow the budget on hosted per-call pricing.
The VDF AI Solution
Personalise and serve at scale — inside your perimeter
Data Sovereignty
Complete Data Sovereignty
Customer data never leaves your perimeter.
Deploy VDF AI entirely on-premises or in your private cloud. No external API calls. No customer profiles, order history, or behavioural data traveling to third-party servers. Customer PII stays exactly where your DPO and security team require it — keeping personalisation inside GDPR and ePrivacy boundaries.
"We can finally personalise with AI without our DPO blocking it — because nothing about our customers leaves our infrastructure."
100%
On-Premises Deployment
Zero external dependencies
GDPR-alignedCustomer-managed keysNo third-party access
Compliance
Compliance Built-In
GDPR, EU AI Act & PCI-aware from day one.
VDF AI provides the governance infrastructure regulated retailers need:
- Complete Audit Trails — every prompt, retrieval, and response logged with full context for DPO and audit review
- PII Boundary Control — customer data processed locally; personalisation stays within GDPR & ePrivacy limits
- Out of PCI Scope — never transmits payment data to third parties, helping keep AI out of cardholder-data scope
- Role-Based Access — scope agents and data across service, merchandising, and marketing teams
- Human-in-the-Loop — review gates for customer-facing content and decisions
Audit-grade
Compliance Ready
GDPR · EU AI Act · PCI DSS
Immutable logsPII boundaryOut of PCI scope
Cost Control
Intelligent Cost Management
AI economics that survive peak trading.
Retail volumes are huge and seasonal. VDF AI delivers:
- Per-Operation Cost Tracking — know exactly what each interaction and channel costs
- Model Routing Optimization — route high-volume routine tasks to small models, reserve frontier models for complex cases
- Budget Controls — set limits by channel, brand, or campaign
- ROI Reporting — tie AI to conversion, deflection, and content velocity
- 40–60% Cost Reduction — compared to traditional cloud AI approaches
40–60%
Cost Savings
vs. hosted cloud alternatives
Per-op trackingTier-aware routingPeak-ready
Where it pays back
Use cases for regulated retail & omnichannel
VDF AI agents and tools
Improve retail workflows with agent-tool networks
Each workflow combines a focused retail agent pattern with the tools needed to retrieve commerce context, respect consent, generate content, analyze demand, and preserve the audit trail.
Service assist
Omnichannel customer service
Agents answer product, order, policy, and return questions across digital, store, and contact-center channels.
Sales Enablement Agent
Private RAGSentiment AnalysisAudit Trail
Explore workflow Brand reviewed Product content generation
Generate, translate, and adapt product copy from PIM data while routing customer-facing text through review.
Content Planning Agent
Document GeneratorOutput EvaluationHuman Approval
Explore workflow Merch assist Catalog and search enrichment
Clean attributes, synonyms, tags, and taxonomy gaps so customers find the right product faster.
Enterprise Search Agent
Private RAGSource CrosscheckReport Compile
Explore workflow Planner assist Demand and inventory analysis
Summarize demand shifts, returns, stockouts, promotions, and allocation risk for planning teams.
Chart Generator Agent
CSV AnalyzerAnomaly DetectSpreadsheet Generator
Explore workflow Consent gated Governed personalization
Create recommendations and journeys only inside consent, fairness, privacy, and brand-policy limits.
Strategy Advisor Agent
Confidence ScorePermission CheckHuman Approval
Explore workflow Store assist Store-ops and associate knowledge
Associates get consistent answers about products, promotions, policies, and exceptions with cited sources.
Enterprise Search Agent
Private RAGCitation VerifyAudit Trail
Explore workflow Under the hood
Technical specifications for retail
| Requirement | VDF AI Capability |
|---|---|
| On-premise deployment | Full on-premises, private-cloud, sovereign-cloud, or air-gapped deployment options |
| Data sovereignty | Models, embeddings, customer & order data remain inside your sovereignty and residency perimeter |
| PII & PCI boundaries | Customer PII processed locally; never transmits payment data to third parties, helping keep AI out of PCI scope |
| Private RAG | Product, order, policy & promotion data stay on-premise inside your governed vector-store boundary |
| Role-based access | RBAC-scoped agents, tools & knowledge across service, merchandising & marketing |
| Model routing | Tier-aware routing keeps high-volume routine tasks on smaller models — frontier models for complex cases |
| Audit logs | Immutable audit logs for prompts, retrievals, tool calls & responses — SIEM export & long-term custody |
| Integration examples | E-commerce platform, OMS, POS, CRM/CDP & PIM integrations via MCP adapters |
| Encryption | At-rest and in-transit, customer-managed keys |
| Authentication | SSO, LDAP, Active Directory, MFA |
| Uptime SLA | 99.9% (Enterprise tier) |
ROI Snapshot
What changes after rollout
−50%
Customer service handling time
40–60%
Lower AI operating costs vs. cloud
10×
Faster product-content production
+30%
Self-service deflection rate
FAQ
Questions retail teams ask
Is VDF.AI compliant with GDPR, the EU AI Act, and PCI DSS for retail?
Yes. VDF.AI deploys fully on-premise or in your private cloud, so customer profiles, order history, and behavioural data never leave your perimeter — which keeps personalisation and service use cases inside GDPR and ePrivacy boundaries. It supports EU AI Act controls for any high-risk use, helps keep generative AI out of scope for cardholder data under PCI DSS by never transmitting payment data to third parties, and logs every prompt, retrieval, and response as immutable audit records.
Can VDF.AI power personalisation and customer service without exposing customer data?
Yes. Because the platform runs inside your environment with private RAG over your own product, order, and policy data, you can build governed personalisation and omnichannel service experiences without sending customer PII to a hosted model. Role-based access and audit trails give your DPO the controls and evidence they need to sign off.
How does VDF.AI handle peak-season scale and cost?
Tier-aware model routing keeps routine, high-volume tasks — product Q&A, order status, content tagging — on smaller, cheaper models, reserving frontier models for complex cases. Combined with per-operation cost tracking and budget controls, that delivers predictable AI economics even through peak trading, at 40–60% lower cost than hosted-cloud approaches.
Why on-premise AI instead of a hosted cloud provider for retail?
Hosted providers require sending prompts and data fragments — customer profiles, order data, behavioural signals — to third-party infrastructure, creating GDPR, ePrivacy, and PCI scoping problems across millions of customers. On-premise AI keeps customer and commercial data inside your boundary: no third-party access, no cross-border transfer questions, no surprise terms-of-service changes.
Ready to deploy AI without risking customer data?
Talk to our team about your service, content, and personalisation requirements.