Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails Training Course
Developing Enterprise AI Agents on Tencent ADP: Integrating RAG, Workflows, and Operational Safeguards is a hands-on program focused on the design, construction, and deployment of enterprise-grade AI agents using the Tencent ADP platform.
This live, instructor-led training session, available both online and onsite, is tailored for intermediate-level solution architects, AI engineers, developers, and technical product teams aiming to leverage Tencent ADP to create enterprise AI agents featuring production-ready RAG, workflow automation, multi-agent coordination, and robust operational guardrails.
Upon completing this training, participants will be equipped to:
- Architect AI agents within Tencent ADP tailored for specific enterprise applications.
- Construct RAG pipelines and knowledge workflows that enhance response accuracy.
- Orchestrate complex workflows and multi-agent interactions to streamline business processes.
- Implement guardrails, monitoring, and operational controls suitable for production environments.
Course Format
- Engaging lectures and facilitated discussions.
- Structured exercises and practical workshops.
- Live, hands-on implementation within a lab environment.
Customization Options
- To explore customized training options for this course, please reach out to us to discuss specific arrangements.
Course Outline
Enterprise AI Agents on Tencent ADP
- Understanding the definition of enterprise AI agents and their value proposition
- Tencent ADP’s capabilities for agent development, knowledge integration, and workflow automation
- Distinguishing between agent-based solutions and standard chat applications
- Exploring common enterprise use cases and key delivery considerations
Designing Agents for Business Processes
- Defining agent roles, operational boundaries, inputs, and outputs
- Selecting between single-agent and multi-agent architectural designs
- Structuring prompts, tool interactions, and business rule logic
- Planning for escalation paths, human review mechanisms, and system reliability
Constructing RAG and Knowledge Workflows
- RAG principles for grounded responses and accessing enterprise knowledge
- Preparing documents, policies, and internal content for effective retrieval
- Designing retrieval flows and response grounding strategies
- Testing and iteratively improving answer quality over time
Orchestrating Workflows and Integrations
- Mapping business processes into structured agent workflows
- Connecting agents to APIs, internal services, and broader enterprise systems
- Managing decision points, approvals, retry logic, and fallback pathways
- Coordinating handoffs between workflow steps and specialized agents
Implementing Operational Guardrails
- Establishing guardrails for security, privacy, compliance, and policy enforcement
- Mitigating risks associated with unsafe output, prompt injection, and data exposure
- Incorporating approval checkpoints, audit trails, and granular access controls
- Designing safe response patterns for high-stakes business scenarios
Monitoring, Evaluation, and Continuous Improvement
- Tracking quality metrics, latency, costs, and workflow success rates
- Evaluating agent behavior across realistic business scenarios
- Troubleshooting common challenges in RAG, workflow, and orchestration layers
- Formulating implementation plans for pilot testing and production rollout
Requirements
- A foundational grasp of generative AI principles and typical enterprise AI applications
- Practical experience interacting with APIs, web applications, or cloud-based ecosystems
- Basic proficiency in programming, system integration, or solution architecture
Target Audience
- Solution architects and technical leads
- AI engineers, application developers, and automation specialists
- Product managers and innovation teams driving enterprise AI initiatives
Open Training Courses require 5+ participants.
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