AI Customer Support Automation
A customer support assistant that answered routine questions and updated order records automatically. Placeholder case study — results to be verified before publishing.
The Challenge
Challenge
The client's support team received hundreds of routine questions daily, many of which were simple order-status and policy questions. Response times were slow and staff spent most of their day on repetitive replies.
(Placeholder challenge text — replace with verified client details.)
The Solution
Solution
We built an AI support assistant that understands intent, retrieves order information, drafts answers, and updates the order database. Complex cases are escalated to humans automatically.
(Placeholder solution text.)
Technology
Next.js, TypeScript, LLM API, MySQL, vector search
Architecture
Architecture
Assistant → Intent understanding → Order lookup (API) → Grounded response → Ticket update → Escalation when confidence is low.
Implementation
Implementation
Rolled out in phases: knowledge base first, then live order lookups, then autonomous ticket updates with human approval.
Results
Results
Metrics to be added once real client data is available. We only publish measured results.
Lessons Learned
Lessons learned
Start with the highest-volume, lowest-risk question type. Measure resolution rates and escalation quality from day one.