AI Agent Customization

What is an AI Agent?

An AI Agent is an intelligent entity that can autonomously understand tasks, plan steps, execute operations, and self-correct. Unlike traditional software, AI Agents do not operate based on fixed programs but rather "understand → think → act" like humans.

What should a usable enterprise AI Agent include?

We will not just create a chatbot. An enterprise-grade AI Agent must be able to access knowledge, invoke tools, adhere to permissions, handle exceptions, and log key operations for team review and continuous optimization.

Capability	Description
Role Boundaries	Clearly define what the Agent is responsible for and what it is not, avoiding unauthorized responses or performing irrelevant tasks.
Knowledge Sources	Access product documentation, SOPs, contract templates, historical tickets, project materials, and databases.
Tool Invocation	Connect to CRM, ERP, OA, ticketing systems, email, WeCom, Lark, or internal APIs.
Human Takeover	Automatically escalate to a human when encountering low confidence, sensitive information, complaints, or high-risk operations.
Observability	Log queries, retrieval sources, tool invocations, generated results, user feedback, and correction records.
Continuous Optimization	Optimize the knowledge base, prompts, process rules, and response templates based on real usage data.

Differences from Traditional Software

Traditional Software	AI Agent
Run based on preset logic	Make autonomous decisions after understanding intent
Can only handle known situations	Can adapt to unknown changes
Fixed functionality, requires development for upgrades	Continuous learning, automatic optimization
Humans adapt to software	Software adapts to humans

Delivery Process

Needs Assessment (1 week): Deeply understand your business scenario and assess AI Agent feasibility.

POC Validation (2-4 weeks): Rapidly build a prototype and validate core capabilities.

Full Development (4-8 weeks): Complete functional development, testing, and optimization.

Deployment & Go-Live (1 week): Deploy to production and train the user team.

Continuous Optimization: Continuously optimize the Agent's performance based on operational data.

Common Implementation Forms

Website & Mini-Program AI Customer Service: Handles pre-sale inquiries, order tracking, after-sales issues, data collection, and ticket creation.

Sales Follow-up Assistant: Automatically compiles customer profiles, generates follow-up suggestions, draft quotes, visit notes, and deal risk alerts.

Internal Knowledge Assistant: Allows employees to query policies, SOPs, project experiences, product materials, and training content via natural language.

Data Analysis Assistant: Connects to databases or BI systems to generate metric interpretations, anomaly root cause analysis, and business recommendations.

Compliance Review Assistant: Assists with consistency and risk checks for contracts, bidding documents, marketing scripts, and customer data.

Data Security and Deployment Methods

Based on customer requirements for data security, budget, and maintenance capabilities, we support SaaS API calls, enterprise private knowledge bases, hybrid cloud deployment, and on-premises private deployment. Sensitive data can be masked before entering the model, the knowledge base is authorized by role, key operations are logged in audit trails, and high-risk tasks must be confirmed by a human before execution.