The Challenge
LumaHarbor Technologies is the client behind this project. A Liverpool technology services business faced increasing support volumes. Its team needed a way to answer common questions quickly while keeping complex issues with human agents.
Customers phrased similar questions differently, making intent recognition important. The platform also needed relevant knowledge-base information, protection for customer data and integration with existing support systems.
The proposed solution
ApexCore Digital’s solution combines natural language processing, knowledge-base search and AI-generated responses. Intent and sentiment analysis help classify requests, while ticket prioritization and agent assistance support the wider service workflow.
The design calls for responses based on available knowledge and conversation context. Requests that cannot be handled with sufficient confidence are routed to human agents. Conversation history and analytics provide visibility into support activity, alongside application and model monitoring.
How the workflow supports the business
The intended support workflow begins by interpreting a customer’s request and searching for relevant knowledge. Ticket classification and prioritization organize the request for the support team, while conversation history preserves context for subsequent interactions. When the system lacks sufficient confidence, escalation gives a human agent a route to take over. This makes the knowledge base a central part of the design. Response quality depends on the relevance of the available information, so model and application monitoring are included alongside the customer-facing conversation experience.
Figures supplied for validation
- 60% reduction in response time.
- 40% reduction in repetitive support tickets.
- More than 85% successful automated query resolution.
- More than 90% intent-classification accuracy.
Technology: React / Angular, Python, FastAPI, LLM / NLP models, PostgreSQL / MongoDB, FAISS / Pinecone, AWS / Azure.
