Question 1

How does AI-powered appliance diagnosis work?

Accepted Answer

Our AI analyzes customer photos, voice descriptions, and error codes to instantly diagnose issues with 80% accuracy. The system continuously learns from repair cases to provide step-by-step solutions in seconds.

Question 2

Which appliance brands can the AI diagnose?

Accepted Answer

Our AI can diagnose appliances from all major manufacturers including Bosch, Siemens, Samsung, LG, Whirlpool, and over 40 other brands. The database covers refrigerators, washers, dryers, dishwashers, and ovens manufactured after 2010.

Question 3

How quickly can Repflow AI be integrated?

Accepted Answer

Integration takes 48 hours. Connect via our REST API or pre-built integrations with popular CRM systems. Most businesses see 80% automation rates within the first week.

Question 4

Is Repflow AI GDPR compliant?

Accepted Answer

Yes, Repflow AI is fully GDPR compliant with data centers in Frankfurt. We provide encrypted storage, automatic data retention policies, and complete audit trails for European businesses.

Question 5

What languages does Repflow AI support?

Accepted Answer

Repflow AI operates in German, English, French, Spanish, and Italian. The AI maintains native-level accuracy across all languages with region-specific terminology.

Question 6

What's the ROI of using Repflow AI?

Accepted Answer

Businesses typically see 60% reduction in support costs and achieve ROI within 2 months. Average resolution time drops from 15 to 3 minutes while first-call resolution increases to 80%.

Question 7

How does the pricing work?

Accepted Answer

Repflow AI offers custom enterprise pricing tailored to your business needs. Our pricing model includes a setup fee and per-resolution pricing for successful support cases, similar to leading support automation platforms. Contact our sales team for a personalized quote based on your volume and requirements.

Question 8

Can Repflow AI handle complex repairs?

Accepted Answer

Yes, the AI handles multi-system failures and identifies cascade issues that single-point diagnostics miss. For complex cases, it seamlessly escalates to human technicians with full context.

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