1.Big Model Insight Agent
Discover potential business opportunities and drive business growth
Based on the semantic understanding and reasoning capabilities of DeepSeek-R1, it enables in-depth exploration of customer needs and precise positioning of business opportunities.
- Deep Contextual Association
Comprehensive analysis of long texts and complex documents, identifying implicit needs across paragraphs and conversations, and capturing unexpressed pain points by customers.
- Domain knowledge enhancement
More proficiently integrating industry knowledge graphs (product manuals, policies and regulations), strengthening the recognition of financial terms, and making the judgment of financial scenarios more accurate.
- Emotional Intention Stratification
By conducting an analysis of emotional intensity (complaint level) and categorizing intentions (consultation/complaint/suggestion), the granularity of priority judgment for demands is enhanced.
Business Value
(Testing and Verification Results of a Shareholding Banking Institution)
Accuracy Improvement: The accuracy rate of requirement extraction has increased by more than 30% compared to the general large model.
Experience Enhancement: The complaint rate has decreased by 30% or more.
Product Innovation: Discovering deep latent needs has facilitated the planning of new product lines.
2.Large Model Quality Inspection Agent (QM Agent)
Comprehensive compliance inspection, achieving dual breakthroughs in cost reduction and efficiency improvement
Relying on the long-sequence modeling capability of DeepSeek-R1, it enables breakthroughs in complex semantic understanding and deep risk reasoning.
- Complex Scene Recognition
DeepSeek can enhance context analysis and accurately identify disguised promised benefits, contradictory statements, and other such scenarios.
- Implicit Attitude Analysis
By integrating deeper semantic and emotional analysis, we enhance the judgment of implicit attitudes such as "lack of service awareness".
- Quality inspection rules evolve automatically
By analyzing user feedback and error cases, we can automatically discover more effective inspection logic, and upgrade keyword matching to a scenario reasoning mode.
Business Value
(Results of a securities company's business test and verification)
Accuracyboost enormously： The rate of missed detections of violations has decreased by over 40%， and the accuracy rate of identifying disguised violations has exceeded 90%.
Cost reduction： The coverage rate of quality inspection has been upgraded from random sampling at 20% to 100% coverage， and the cost of manual review has been reduced by 70%.
Experience optimization： Through the improvement of the standardization of service language， the customer complaint rate has decreased by 25%-30%.
3.Large Model Call Agent (Virtual Agent)
Shift from basic question answering to deep services
DeepSeek-R1 enables multi-round conversation management, real-time knowledge retrieval, and improvement of voice interaction capabilities.
- Enhanced understanding and reasoning of complex intentions
Supports the decomposition of users' multi-level intentions and generates logical reasoning responses.
Example: In customer self-service consultation, it can automatically combine the complex terms in insurance and generate comparative analysis in plain language, such as "Product A has lower risks but a lower upper limit of return."
- Multi-source knowledge linkage
In the conversation, dynamically link the product manual, the latest policies, and the user's historical records to generate personalized responses.
- Personification Responses
In the telephone scenario, the dialogue interaction should be more similar to the tone and colloquial expressions of a real customer service representative, providing a personalized experience.
Business Value
(Testing and Verification Results of a Life Insurance Business)
Improvement in resolution rate: The first-time resolution rate of issues increased from 65% to 85%.
Increase in marketing conversion: The customer conversion rate after a single conversation increased by 30%.
Optimization of labor costs: The rate of transferring to manual processing decreased by 50% or more.
4.Large Model Knowledge Assistant (Knowledge Copilot)
Accurate responses, intelligent knowledge management
DeepSeek-R1 enables significant improvements in dimensions such as answer generation accuracy.
- Deep Semantic Retrieval and Cross-Document Reasoning
Deeply analyze the complex query, automatically identify conflicts among multiple versions of documents, and extract highly accurate answers from scattered documents.
- Active Learning of High-Frequency Knowledge
Based on recent frequently asked questions, automatically extract knowledge summaries and proactively recommend them to customer service representatives.
Business Value
Accurate responses in highly specialized fields: The accuracy rate of answers to industry-specific complex questions reaches 95% or higher.
5.Large Model Agent Assistant (Agent Copilot)
Real-time strategy recommendation, achieving dual improvements in efficiency and experience
DeepSeek-R1 enables breakthroughs in dimensions such as the accuracy of real-time strategy recommendations, dynamic knowledge integration, and decision support in complex scenarios.
- Scene Script Recommendation
It conducts a comprehensive analysis of various dimensions such as customer emotions, conversation context, historical records, business rules, and the latest policies, and dynamically adjusts the strategies.
For instance, when it is identified that the customer's stance shifts from "comparison hesitation" to "price sensitivity", the Cloopen AI agent assistant can promptly switch the script strategy, moving from recommending financial products to guiding the application for discounts.
- Exploration of Historical Best Practices
By integrating deeper cross-session knowledge correlations, we extract the best practices from a large number of historical conversations, such as the communication strategies used by a top-notch customer service representative when handling "package downgrade complaints".
- Voice emotion enhancement analysis
In the context of telephone customer service, hidden emotions can be identified through features such as speaking speed and tremors, and appropriate soothing strategies can be recommended.
Business Value
Service Efficiency: Efficiency in handling complex issues has increased by 40%.
Marketing Efficiency: The success rate of retaining high-value customers has increased by 25%.
Personnel Efficiency: The number of calls handled by agents in a single day has increased by 50%.
6.Large Model Coaching Agent
Transition from standard drills to practical capabilities
DeepSeek-R1 enables enhanced capabilities such as the generation of more industry-specific coaching question banks and deliberate training.
- Integration of enterprise expertise:
Based on enterprise private data (such as historical customer complaint cases, product manuals), an industry-specific question bank is automatically generated.
- Fine-grained capability diagnosis:
Through dialogue performance analysis, multiple dimensions of capability items such as "emotional soothing efficiency", "policy reference accuracy", and "smoothness of multitasking switching" are examined, generating a more precise capability profile.
- Tailored training scripts for each individual:
Based on the analysis of the agent's capabilities, a personalized practice script is generated to facilitate deliberate practice.
Business value
Quantification of capability improvement: Key performance indicators for agents (such as resolution rate per interaction) have been improved by an average of 40%.