DevPilot

Logistik

Support, der nicht ausbrennt

Wie wir 75% der Last von zwei Operatoren genommen haben — und Kunden wieder schnelle Antworten bekommen.

Ergebnis
0%
Zeitrahmen
ROI 1,5 Mon
Kategorie
Logistik
Was war

800 E-Mails pro Woche, 2 Mitarbeiter brennen aus und kommen nicht hinterher. Kunden warten Stunden.

A logistics company received 800+ email tickets per week: lost cargo, damage, delays, document requests.

Two operators worked 10-hour days and replied 4–6 hours late even to routine questions. Customers were churning to competitors.

Hiring another operator was hard: the niche labour market is thin, onboarding takes 3 months.

Was wir gemacht haben

AI-Agent klassifiziert Tickets und antwortet mit Templates, eskaliert Schwieriges an den Menschen. Ersparnis $5 400 / Mon.

  1. 01

    Analysed 4,000 past tickets and identified 12 main request types with template answers.

  2. 02

    Built an AI agent on the Claude API with RAG over the contracts and template-answer knowledge base.

  3. 03

    Wired up n8n for classification: 75% of tickets close automatically, complex ones escalate to humans with full context and a draft reply.

  4. 04

    Added a quality-control dashboard: every auto-reply can be reviewed and rolled back.

Was sich geändert hat

Ergebnis

75% of tickets close automatically in 30 seconds instead of 4 hours

Payroll savings: $5,400/month (one operator no longer needed)

ROI reached 1.5 months after launch

Customer NPS jumped from 31 to 58 in a quarter

Stack
Claude APIPostgresn8nFastAPIReact

Nächster Case

Vom Seed-Round zur Production

SaaS founder

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