Our Cases

Problem

500+ delivery requests daily. Manual sorting and routing took 4 hours by 3 operators. Priority errors were frequent — urgent requests got lost among regular ones.

Solution

Implemented AI auto-classification module: NLP text analysis, priority detection, automatic routing to the right dispatcher. Integration with existing system via API.

Results

• -40% ticket processing time
• -90% routing errors
• Saving 3 man-hours per day
• ROI in 2 months

Problem

Lawyers spent 60% of time on routine: finding precedents, preparing standard documents, answering typical client questions. High hourly cost with low margins on routine tasks.

Solution

Created a RAG-based AI assistant trained on 10,000+ legal documents. The bot answers client questions, drafts documents and finds relevant precedents.

Results

• -60% time on routine tasks
• +25% client capacity
• Client response in 30 seconds vs 2 hours
• 300% ROI in first year

Problem

Support couldn't handle the volume: average response time — 4 hours. 70% of questions were typical (order status, returns, delivery). Customers were leaving for competitors.

Solution

Launched an AI chatbot for first-line support with CRM and tracking integration. The bot resolves 70% of inquiries independently, passes the rest to operators with context.

Results

• +35% response speed
• 70% of inquiries resolved without operator
• -45% support workload
• NPS grew from 42 to 67

Problem

Management received reports with a 3-5 day delay. No unified KPI view across departments. Equipment failures caused 8-12 hour downtimes.

Solution

Implemented AI analytics: real-time dashboards, KPI forecasting, and predictive equipment maintenance based on sensor data.

Results

• Real-time reports instead of 3-5 days
• -30% equipment downtime
• +15% OEE (overall efficiency)
• Failure prediction 48 hours ahead