
Channel-ready support agent
Repeat tickets flood desks during port and retail peaks. The agent answers order status and policy questions in the first message. Containment rises while staff handle only exceptions. We use retrieval over live knowledge so answers stay current. Webhook actions open tickets when needed. This cuts average handle time without new hires. Monitoring shows escalation reasons weekly so you improve the gaps.

Logistics status bot
Drivers and brokers ask the same ETA questions all day. A focused bot pulls tracking data and returns plain updates. False waits drop because the model never invents numbers. We chose structured tool calls over free text for reliability. Integration uses existing TMS APIs so no duplicate entry appears. Dispatchers reclaim hours previously lost to chat. The bot works across SMS and web for field crews near the shipyard.

Recommendation layer
Browsers leave when they cannot find the right SKU fast. The layer pairs intent with product attributes and past preference signals. Conversion lifts because suggestions feel personal yet stay in stock. We built the logic like the beauty agent case using clear ranking rules. LLM output only formats the final short list. Merchandisers control the rules without code changes. Results appear in attach rate within the first campaign cycle.

Internal knowledge desk
New hires slow teams while they hunt for policy PDFs. An internal agent answers from approved SOPs only. Accuracy stays high because retrieval never leaves the private corpus. We picked vector search plus citation so every claim shows its source. Managers edit documents and the agent refreshes overnight. Onboarding time shrinks for warehouses in Hampton Roads. Audit trails keep compliance reviews short.

Handoff and analytics pack
Blind escalations frustrate both customers and agents. The pack attaches full history and intent tags before a human joins. First-contact resolution improves because context is complete. We instrument containment, latency, and cost per session from day one. Dashboards feed your existing BI tools. Product owners see which intents still fail and fix the content. This closes the loop instead of guessing at monthly reviews.