AI Agents & RAG Training
& Enterprise AI Search

Agent Architecture Complexity

Designing reliable AI agent systems requires deep expertise in agent loops, tool use, memory management, and multi-agent coordination that goes far beyond basic LLM API usage.

RAG Implementation Challenges

Building production-grade RAG systems requires expertise in vector databases, embedding models, chunking strategies, retrieval optimization, and context window management for accurate enterprise AI search.

Multi-Agent Orchestration

Coordinating multiple specialized AI agents — planner, executor, critic, and tool agents — requires sophisticated orchestration patterns and failure handling strategies for reliable enterprise automation.

Agent Security & Safety

AI agents with tool access and autonomous decision-making introduce new security risks including prompt injection, unauthorized actions, data exfiltration, and uncontrolled resource consumption.

RAG Quality & Accuracy

Achieving high retrieval accuracy in enterprise RAG systems requires advanced techniques including hybrid search, reranking, query expansion, and continuous evaluation to prevent hallucinations.

Enterprise AI Search at Scale

Scaling AI-powered enterprise search across large document repositories, multiple data sources, and thousands of users requires architecture expertise in vector infrastructure and retrieval optimization.

AI Agent Fundamentals

Master AI agent architecture including agent loops, reasoning patterns, tool use, memory systems, and the ReAct framework for building autonomous AI agents that complete complex multi-step tasks.

Multi-Agent Systems

Design and implement multi-agent systems with specialized agents, agent communication protocols, orchestrator-worker patterns, and collaborative AI workflows for complex enterprise automation.

RAG Architecture

Build production-grade Retrieval-Augmented Generation systems with vector databases, embedding models, chunking strategies, hybrid search, reranking, and context optimization for accurate AI responses.

Enterprise AI Search

Implement enterprise AI search solutions with semantic search, hybrid retrieval, knowledge graph integration, and multi-source RAG for intelligent document discovery and knowledge management.

Agent Security & Guardrails

Implement AI agent security controls including tool permission management, action validation, output filtering, rate limiting, and responsible AI guardrails for safe autonomous AI operations.

RAG Evaluation & Optimization

Apply RAG evaluation frameworks including RAGAS metrics, retrieval accuracy testing, answer faithfulness scoring, and continuous monitoring for production RAG quality assurance.

LangChain & LlamaIndex

Build AI agents and RAG systems using LangChain agents, LangGraph for stateful workflows, LlamaIndex for data connectors, and custom tool integrations for enterprise AI applications.

Cloud AI Agent Platforms

Deploy AI agents on enterprise platforms including Azure AI Agent Service, AWS Bedrock Agents, OCI AI Agents, and Google Vertex AI Agent Builder with enterprise security and compliance.

Design and implement production-grade AI agents with tool use, memory management, reasoning loops, and error handling for reliable autonomous task completion in enterprise environments.

Architect multi-agent systems with specialized agent roles, orchestration patterns, inter-agent communication, and collaborative workflows for complex enterprise AI automation.

Build production RAG systems with vector databases (Pinecone, Weaviate, pgvector), embedding models, hybrid search, reranking, and context optimization for accurate enterprise AI responses.

Implement agent security controls including tool permission management, action sandboxing, output validation, and responsible AI guardrails for safe enterprise AI agent operations.

Apply RAGAS evaluation framework, implement retrieval accuracy testing, measure answer faithfulness, and build continuous monitoring pipelines for production RAG quality assurance.

Deploy AI agents and RAG systems on Azure AI Agent Service, AWS Bedrock Agents, OCI AI Agents, and Google Vertex AI with enterprise security, compliance, and observability.

AI/ML Engineers

Engineers building AI-powered applications who need expertise in agent architecture, RAG systems, and multi-agent orchestration for production enterprise AI deployments.

Software Architects

Architects designing enterprise AI systems who need to understand agent patterns, RAG architecture, vector infrastructure, and AI platform integration for scalable AI solutions.

Data Engineers

Data engineers building data pipelines for AI who need expertise in vector databases, embedding pipelines, document processing, and RAG data infrastructure.

Backend Developers

Backend developers integrating AI agents into enterprise applications who need expertise in agent APIs, tool development, and AI workflow integration patterns.

Enterprise AI Teams

Enterprise AI teams deploying autonomous AI systems who need comprehensive training in agent governance, security, evaluation, and responsible AI practices.

Knowledge Management Teams

Teams building enterprise knowledge bases and AI search systems who need RAG expertise for intelligent document retrieval and knowledge management automation.

• Agent Architecture
• ReAct Framework
• Tool Use Patterns
• Memory Systems
• Agent Loops

• LangChain Agents
• LangGraph Workflows
• Custom Tool Development
• Error Handling
• Agent Testing

• Agent Orchestration
• Specialized Agents
• Agent Communication
• Planner-Executor Pattern
• Collaborative Workflows

• Vector Databases
• Embedding Models
• Chunking Strategies
• Indexing Pipelines
• Context Management

• Hybrid Search
• Reranking
• Query Expansion
• HyDE
• Multi-Query Retrieval

• Semantic Search
• Multi-Source RAG
• Knowledge Graphs
• Document Processing
• Search Optimization

• Tool Permissions
• Action Validation
• Prompt Injection Defense
• Output Filtering
• Responsible AI

• RAGAS Metrics
• Retrieval Accuracy
• Answer Faithfulness
• Continuous Monitoring
• Production Deployment

AI Agents Fundamentals

2-day foundational training covering AI agent architecture, tool use, LangChain agents, and hands-on agent building with GPT-4 and Claude.

RAG Systems Workshop

Focused 2-day RAG workshop covering vector databases, embedding models, hybrid search, reranking, and production RAG deployment with evaluation.

Enterprise AI Agents & RAG

Comprehensive 4-day program covering AI agents, multi-agent systems, RAG architecture, enterprise AI search, security, and production deployment.

Corporate AI Enablement

Customized AI agents and RAG training aligned to your AI platforms, use cases, and enterprise AI architecture requirements.

Build a production AI agent with LangChain including custom tool development, memory management, error handling, and multi-step task completion for an enterprise automation use case.

Implement a multi-agent system with LangGraph featuring a planner agent, executor agents, and a critic agent for automated research and report generation.

Build a RAG pipeline with Pinecone vector database, OpenAI embeddings, document chunking, and semantic search for an enterprise knowledge base application.

Implement hybrid search combining dense and sparse retrieval, add a reranking layer with Cohere Rerank, and apply query expansion for improved RAG accuracy.

Test AI agents against prompt injection attacks, implement tool permission controls, configure output validation, and build responsible AI guardrails for production agent deployment.

Implement RAGAS evaluation pipeline measuring context precision, context recall, answer faithfulness, and answer relevancy for continuous RAG quality monitoring.

Azure AI Engineer Associate (AI-102)

Azure AI certification covering Azure AI Agent Service, AI Search, and RAG application development.

AWS Machine Learning Specialty

AWS ML certification covering Bedrock Agents, Knowledge Bases, and AI application development.

Google Professional ML Engineer

Google Cloud ML certification covering Vertex AI Agent Builder and enterprise AI search.

OCI Generative AI Professional

Oracle Cloud Generative AI certification covering OCI AI Agents and enterprise RAG deployment.