Agentic AI is the fastest-growing segment in enterprise AI in 2026. Most developer teams are still building with GenAI basics. This 3-day bootcamp takes your team from GenAI-capable to agentic AI-ready — building and deploying autonomous systems on your real business use cases.
Gartner predicts that 40% of enterprise applications will include task-specific AI agents by end of 2026 — up from less than 5% in 2025. Deloitte reports that 50% of organisations have identified multi-agent workflows as a key focus area. The enterprise AI stack is moving from "AI that answers questions" to "AI that completes tasks."
The difference matters enormously for your team. A developer who can build a RAG system cannot automatically build a multi-agent workflow. Agentic AI requires a fundamentally different architecture mindset — tool orchestration, state management, human-in-the-loop design, and failure handling at every step.
Most corporate AI training in India is still teaching GenAI basics — prompt engineering and simple LLM APIs. The Trendwise Agentic AI Bootcamp is built specifically for the step beyond: autonomous systems that act, not just answer.
Prompt engineering · RAG · LLM APIs · AI-assisted workflows · Copilot tools
AI that answers questions and assists humans with tasks.
Multi-agent systems · Tool orchestration · n8n automation · MCP · Voice agents · Autonomous deployment
AI that completes tasks autonomously — without human input at every step.
MORNING
What makes AI "agentic" · Tool use and function calling · Agent design patterns · ReAct, Plan-and-Execute, and multi-agent orchestration · Human-in-the-loop architecture · State management for long-running agents
AFTERNOON
n8n fundamentals for enterprise automation · Building multi-step AI workflows in n8n · Connecting n8n to enterprise APIs and databases · Error handling and retry logic · Live build: automated enterprise workflow on real business process
MORNING
Claude Code for agentic development · MCP architecture and enterprise integration · Building custom MCP servers · Connecting agents to internal enterprise systems · Multi-agent coordination with Claude Code · Live build: MCP-integrated enterprise agent
AFTERNOON
LangGraph for stateful multi-agent workflows · AutoGen for agent collaboration · Supervisor and hierarchical agent patterns · Agent memory and context management · Live build: multi-agent system for a real enterprise use case
MORNING
Voice agent architecture with ElevenLabs · Integrating voice agents with enterprise workflows · Production deployment patterns · OpenTelemetry for agent monitoring · RAGAS evaluation for agentic systems · Governance and responsible deployment
AFTERNOON
Capstone project: teams build and present a complete agentic system — from use case selection through multi-agent architecture, MCP integration, and production deployment. Panel review and feedback.
What participants leave with: A deployed multi-agent system built on a real business use case · Working n8n automation workflows · MCP-integrated enterprise agents · A 30-day deployment roadmap · The confidence to design and ship agentic AI systems independently.
| Industry | Agentic AI use cases covered in bootcamp |
|---|---|
| BFSI | Fraud detection agents · Claims processing automation · Compliance monitoring · Document intelligence pipelines |
| IT Services & GCCs | AI-augmented code review · Client delivery automation · Multi-agent project management · Knowledge base agents |
| Manufacturing | Predictive maintenance agents · Quality control automation · Supply chain intelligence · Safety monitoring systems |
| Healthcare & Pharma | Clinical documentation agents · Medical knowledge management · Regulatory compliance automation · Research synthesis |
GenAI training covers prompting, RAG, and LLM APIs — tools for working with AI. Agentic AI training covers multi-agent system design, tool orchestration, n8n automation, and deploying AI that operates autonomously. Most enterprises should complete GenAI training before this bootcamp. We always assess capability level before recommending.
Participants should be comfortable with Python, basic APIs, and have some familiarity with LLMs (either from prior GenAI training or self-study). The bootcamp builds from agentic fundamentals but moves fast — prior GenAI exposure is strongly recommended.
Yes — in-person delivery is available across India. Remote delivery is available for teams in UAE, Singapore, the UK, and other markets globally. All programs can be delivered in-person, virtually, or in a hybrid format.
n8n · Claude Code · MCP (Model Context Protocol) · LangGraph · AutoGen · ElevenLabs (voice agents) · OpenTelemetry · RAGAS. All tools are customised to the client's existing tech stack where possible.