Connect a large model with your knowledge base, product library, historical conversations, and multilingual auto translation to build customer service capability for pre-sales, product Q&A, cross-language inquiries, and common after-sales questions.
The system builds answer boundaries around knowledge, product facts, merchant rules, service style, and human feedback to reduce unsupported model guesses.
Upload chat logs, company introductions, product material, and after-sales rules to extract knowledge, style, and business prompts.
Answers prefer knowledge and product facts first. If evidence is insufficient, the system asks a follow-up or hands off.
Website JS, WeChat Customer Service, and official accounts share the same model, knowledge, and human collaboration logic.
Human replies, knowledge gaps, and test cases keep accumulating so the service model becomes more stable over time.
The system does more than answer questions. It turns your knowledge, products, and human experience into reusable service capability.
Upload FAQs, documents, product facts, and chat history.
Extract valuable Q&A into a maintainable knowledge base.
Make AI reply with your brand tone and service standard.
Bind apps to handle product Q&A, pre-sales, and after-sales.
Escalate complex issues and reuse human replies as training data.
Knowledge, products, training, live service, multilingual auto translation, and chat logs become parts of one model training system.
Understand natural customer questions beyond keyword matching.
Turn FAQs, rules, and human replies into searchable knowledge.
Answer prices, stock, specs, selling points, and policies from configured facts.
Train replies that match your brand voice and team behavior.
Let AI handle repeat questions while complex issues move to agents.
Translate visitor messages for agents and translate agent replies back into the customer language automatically.
Extract new Q&A from chat logs and fill model knowledge gaps.
Configure website widgets, WeChat service, official accounts, and external APIs in one place.
Review conversations, handoffs, knowledge gaps, and token usage to improve service quality.
Keep human agents focused on judgment, exception handling, and empathy.
Answer promotions, shipping, purchase advice, and service process questions.
FrequentUse product facts for specs, prices, stock, selling points, and policies.
FrequentHandle returns, warranty, logistics, and other standard policies.
FrequentEscalate complex intent, complaints, or sensitive questions to agents.
FrequentStart with one knowledge base, product library, and service app, then train your own AI customer service model step by step.