AI support assistant that answered, summarized, and routed customer issues
Nirvigo built an AI customer support assistant that answered common customer questions, summarized tickets, and routed unresolved issues to the right team.
- Client
- D2C commerce brand
- Industry
- E-commerce and customer support
- Project
- AI support automation
- Primary service
- AI Automation & Agentic AI
Suggested metrics for mock layout — placeholder/demo numbers.
50 percent reduction in repetitive tickets
40 percent faster first response time
24/7 customer query handling for common issues
12 support intents mapped
What needed solving
Falah Commerce was receiving repeated customer questions about orders, returns, product details, shipping timelines, and payment confirmations. Support agents were spending too much time answering repetitive queries and manually routing edge cases.
The team wanted to:
- Reduce repetitive customer support workload
- Improve first response time
- Keep answers consistent
- Avoid fully autonomous risky responses
- Escalate complex issues to humans
- Understand support trends
Nirvigo built a guarded AI assistant connected to approved knowledge sources and support workflows.
- 01Collected FAQs, policy pages, product data, and support categories.
- 02Created an approved knowledge base.
- 03Built AI response workflows with escalation rules.
- 04Added intent detection and ticket summarization.
- 05Created analytics for common query types.
- 06Set up monitoring and review logs.
What shipped
- AI support assistant
- Knowledge-base search
- Ticket summarization
- Escalation rules
- Agent handover
- Response quality logs
- Support analytics dashboard
Tools used in this build
- Next.js
- Node.js
- AI assistant API
- Vector database
- PostgreSQL
- Support ticket integration
- Cloud logging
The assistant helped us answer routine questions faster while keeping humans involved for sensitive cases.
Layla Al-Mansouri
Head of Customer Experience, Falah Commerce
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