It is not a "tool + AI", but a native operation platform of "AI driven + manual cover"
Instead of superimposing AI on traditional software, it is designed with Agent as the core from the first line of code. The group is the operation field, the agent is the operation team, and the data is the operation fuel.
The business database provides facts, the business knowledge base provides cognition, and the Context engine provides decision-making wisdom. The collaboration between the three data libraries allows the Agent to understand the business better the more it is used.
The traditional client + management backend is no longer needed. The group itself is the operation backend, the data agent pushes the analysis in real time, and the operation agent automatically executes the strategy.
Discover the web pages, tools, and applications shared by the channel, and the data will automatically flow back to the group. Agent automatically optimizes and iterates based on data, and the entire process runs with AI.
Real estate, catering, education, e-commerce, automobiles, medical care, finance... a set of architecture, industry vertical Agent matrix configured on demand.
Every customer interaction is precipitated into data assets, and every operational decision optimizes the context, forming a positive cycle of "data → insight → action → data".
Five-layer architecture: Data Base → AI Engine → Agent Matrix → Group Operation Layer → Application Ecological Layer
Business owners only need to provide three key databases to form a closed loop with the private agent community and operations group.
In-group natural language
AI engine parses intent
Customer portrait + business status
RAG matches best reply
Match goods/services in real time
Accurate replies to thousands of people
Interaction→Context evolution
The group is the private domain, and the agent is the operation team - each private domain group has an "AI operation team that never goes offline"
| Agent role | Responsibilities | core competencies | Trigger condition |
|---|---|---|---|
| 🎯Customer Service Agent | Respond immediately to customer inquiries | Intention recognition, demand matching, emotional comfort, intelligent conversion to artificial intelligence | Customer @Agent or send business related messages |
| 📊 Data Agent | Push data insights in real time | Conversion funnel analysis, customer churn warning, ROI report, heat map | Scheduled push/abnormal indicator trigger |
| 📢 Operation Agent | Automate operational strategies | Event push, coupon issuance, content distribution, fission guidance | Marketing Calendar/Event Trigger/AI Decision-making |
| 🔍 Insight Agent | Uncover deep customer needs | Behavior analysis, demand forecasting, competitive product monitoring, trend discovery | Data accumulation reaches threshold/periodic analysis |
| 🛡️ Compliance Agent | Ensure content security and compliance | Sensitive word filtering, advertising identification, privacy protection, audit logs | All messages are filtered in real time |
Breaking the traditional separation logic of "client + management backend", the group itself is the native operation center of AI.
The data agent automatically pushes key indicator cards every day/hour: new customers, activity rate, conversion rate, GMV, and customer churn warning. Real-time alerts on abnormal indicators.
Operations staff directly ask questions in the group: "Which group has the highest conversion rate this week?" "What are the common characteristics of customers who lost last month?" The data agent returns the analysis results in seconds.
The operation staff issued instructions in the group: "Push weekend house viewing activities to the high-tech zone group" and "Send exclusive discounts to gold card members who have been silent for 7 days", and the operation agent automatically executed them.
After the activity is pushed, the data agent tracks the open rate, click rate, and conversion rate in real time, and automatically generates effect analysis cards and pushes them to the management group.
Insight Agent analyzes historical data and automatically generates optimization suggestions: "It is recommended to adjust the push time from 10:00 to 14:00, and the open rate is expected to increase by 23%."
The Agent provides data support and suggestions for major decisions (such as pricing adjustments, large refunds), and the Agent executes them immediately after manual confirmation in the group.
Application distribution → Data reflow → AI iteration — from "daily disposable software" to "continuously evolving intelligent applications"
Agent generates an event adoption page in the group with one click and automatically publishes it to the discovery channel. User access data and form submission data flow back to the operations management group in real time.
Agent automatically generates and distributes demand research, satisfaction survey, and market research forms. The recycling data is analyzed instantly, and the Insight Agent automatically generates reports.
Calculator, reservation system, member query, points redemption and other lightweight applications. There is no need to develop a backend, and data is managed directly within the group.
Marketing interactive games such as lottery draws, quizzes, and group games. Participation data is pushed to the management group in real time, and the Agent automatically analyzes the participation rate and conversion effect.
Agent instantly generates a visual data analysis page and shares it to the discovery channel for the team to view. Data is updated in real time, no need to refresh manually.
Brand display station, product catalog station, recruitment page, etc. It goes online immediately after deployment, and user data and access data automatically flow back to the group.
Full-chain intelligent operation: data collection → insight generation → strategic decision-making → automatic execution → effect verification → Context evolution
| stage | input | AI processing | output | artificial role |
|---|---|---|---|---|
| 1. Data collection | Group chat messages, user behavior, transaction data, application data | Real-time ETL + structured storage | Unified data lake | No need to intervene |
| 2. Insight generation | Unified data lake | Pattern recognition + anomaly detection + trend analysis | Push the insight card to the management group | reading comprehension |
| 3. Strategic decisions | Insight + Context + Historical Effect | Multi-objective optimization + A/B plan generation | Strategic suggestions (including expected results) | Approval confirmation |
| 4. Automatic execution | Confirmed strategy | Agent orchestration + multi-group parallel execution | Marketing reach/content push/application update | Monitoring anomalies |
| 5. Effect verification | Post execution data | Attribution analysis + ROI calculation + comparison benchmark | Performance reports are pushed to the management group | Review decision |
| 6. Context evolution | Whole process data | Knowledge extraction + rule update + model fine-tuning | Context library updated, Agent capabilities upgraded | No need to intervene |
Customer consultation responses, regular information push, data report generation, automatic labeling, and automatic SOP execution. No manual intervention is required.
Marketing activity push, discount strategy adjustment, customer group changes, and application content updates. AI suggestions + manual one-click confirmation.
Pricing strategy changes, large refund approval, contract terms modification, and release of sensitive content. AI provides data support and humans make the final decision.
One architecture, adaptable to multiple industries - The following are Agent community operation scenarios in four typical industries
📊 Data Agent push:
• There are 12 new inquiries for the high-tech zone group today
• Two-bedroom demand accounts for 68%, and the budget is concentrated at 3000-4000
• Suggestion: Increase the supply of housing in this area
🔍 Insight Agent recommendations:
• Demand around software parks continues to rise +23%
• It is recommended to launch the special activity of "Programmer Residence Plan"
📊 Data Agent push:
• Reached 2,340 people during membership day event
• Mango Smoothie has a 34% click-through rate and a 12% conversion rate
• Gold members have the highest response rate of 45%
⚡ Operation Agent automatically executes:
• Upgrade reminders have been pushed to Silver Card members
• Seats reserved for high-frequency customers
📊 Data Agent push:
• Remaining quota for third grade mathematics class 5/30
• This week’s consultation conversion rate is 28%
• Audition → registration conversion rate 65%
🔍 Insight Agent recommendations:
• There is a strong demand for third-grade mathematics, and it is recommended to open a second period
• It is recommended to start the fission activity of "old with new"
📊 Data Agent push:
• Repurchase reminder reached 856 people
• Instant conversion rate 18% (industry average 5%)
• Rejuvenating Essence 2.0 Today’s GMV ¥41,072
⚡ Operation Agent automatically executes:
• Arranged 48h secondary contact for unresponsive customers
• Updated customer buying cycle model
An intergenerational leap from "tools + AI assistance" to "AI-Native full-chain operation"
| Dimensions | WeChat assistant | Chenfeng SCRM | Tanyu Technology | PrivateAI 2.0 |
|---|---|---|---|---|
| Architecture | Tools + AI assistance | SCRM+Basic Speaking Skills | E-commerce AI customer service | AI-Native Agent Architecture |
| Group chat capability | Group sending + tag grouping | Basic group management | Only 1v1 customer service | Group chat intention recognition + multi-Agent collaboration |
| data base | Basic data of Qiwei | CRM data | E-commerce data | Unified base for three major databases |
| Operation background | Traditional Web backend | Traditional Web backend | Traditional Web backend | Group is the backend, natural language operation |
| Application ecology | None | None | None | Discovery Channel application ecological linkage |
| AI decision-making | Mainly manual decision-making | rules engine | Basic recommendation | AI automated decision-making + manual approval |
| Industry coverage | General retail | Universal | E-commerce only | Universal + Vertical Agent Matrix |
| self-evolution | None | None | None | Context continues to evolve, and the more you use it, the smarter it becomes. |
Three-stage progressive implementation: single-industry verification → multi-industry expansion → ecological scale-up
Single industry verification
Multi-industry expansion
Ecological scale
SaaS subscription + industry solutions + value-added services three-tier revenue structure
three data libraries are connected, the Agent community operates automatically, and the group is the backend.
From diagnosis to delivery, from plan to support.