AI Customer Support & RAG Platform — WineSpot.ai
Overview
Design and delivery of an AI-powered customer support platform for wineries and DTC wine brands, enabling accurate, context-aware responses using retrieval-augmented generation (RAG) and cloud-native infrastructure.
The platform supports customer-facing AI agents across multiple communication channels and is designed to operate reliably under fluctuating, seasonal demand.
Focus areas
- AI-driven customer support platforms
- Retrieval-augmented generation (RAG)
- Consolidation of customer-specific business knowledge
- Cloud-native microservices on Kubernetes
- Observability, scalability, and production operations
Context
Wineries and DTC wine brands face recurring peaks in customer inquiries related to wine club memberships, shipments, orders, events, and policies. Support teams are typically small, while customer expectations for fast and accurate responses are high.
WineSpot.ai was designed to address these challenges by providing a centralized AI platform capable of delivering consistent, up-to-date information to end customers, while integrating with existing winery systems and content sources.
Challenges
- High volume of repetitive customer inquiries during shipment and release cycles
- Business-critical information distributed across websites, documents, policies, product catalogs, events, memberships, CRM systems, and internal tools
- Delivering accurate, context-aware responses based on customer-specific data
- Keeping customer-facing knowledge continuously up to date as content changes
- Meeting scalability, reliability, and observability requirements in a cloud-native production environment
Solution
- Designed and implemented a microservices-based AI platform deployed on Azure Kubernetes Service (AKS), backed by Azure-managed databases
- Implemented retrieval-augmented generation pipelines with near real-time ingestion using website crawlers, REST APIs, and webhook-based updates
- Built centralized, self-hosted prompt management to enable versioning, governance, and controlled rollout of prompt changes
- Implemented autoscaling, replication, and dynamic traffic routing using Kubernetes ingress controllers
- Established end-to-end observability across metrics and logs using Prometheus, Grafana, Datadog, and OpenSearch
Outcome
- Production-ready AI customer support platform serving real winery use cases
- Accurate, up-to-date responses grounded in consolidated business information
- Reduced operational burden on winery staff during peak support periods
- Stable, scalable cloud-native operations on Azure Kubernetes infrastructure
- Reusable platform foundation for additional AI-driven customer experience features
Why this mattered
This engagement demonstrated how retrieval-augmented generation can be applied effectively in customer-facing scenarios where information freshness, correctness, and domain specificity are critical.
By consolidating customer-specific business knowledge from multiple sources into a governed AI platform, WineSpot.ai enabled wineries to deliver consistent, high-quality customer support without increasing operational headcount, while establishing a scalable foundation for future AI-driven services.