Corporate AI training
Agentic AI corporate training for teams that have to ship it
Hands-on programmes covering agentic workflows, LangGraph, CrewAI, RAG and MCP — part of 120+ trainings delivered to 1500+ professionals, on-site anywhere in India or remote.
The approach
Most AI training stops at "here is a prompt". That leaves a team able to demo and unable to deploy. These programmes go the other way: every module ends with something running that the team can maintain after I leave.
I run them alongside leading application development at Signify, where I architect multi-agent systems in production. The labs come out of that work, not a slide library.
Curriculum
What the programme covers
Agentic workflows with LangGraph
Graph-based control flow, state, checkpoints and human-in-the-loop — the architecture that makes multi-step agents reliable instead of impressive once.
- LangGraph
- State machines
- Human-in-the-loop
Building agents with LangChain & CrewAI
Chains, tools, memory and multi-agent crews assembled into systems that do a defined job — with the observability to work out why they failed.
- LangChain
- CrewAI
- Tool use
RAG pipelines that actually retrieve
Chunking, embeddings, retrieval strategy and evaluation. Agentic RAG for when a single lookup is not enough.
- RAG
- Embeddings
- Evaluation
MCP and tool integration
Wiring models into real systems through the Model Context Protocol — the boundary work that turns a chatbot into something operationally useful.
- MCP
- Integrations
- OpenAI API
LLMOps and AI-assisted development
Deployment, monitoring, cost and evaluation in production — plus getting real throughput from AI coding tools without accumulating debt.
- LLMOps
- Monitoring
- Developer tooling
Judgement: where AI does not belong
The module that saves the most money. Cost, latency, correctness and risk — deciding which problems deserve a model and which deserve a function.
- Cost
- Risk
- Responsible AI
Who it’s for
- Engineering teams moving from AI demos to production systems
- Enterprises setting internal standards for AI use
- Product teams evaluating agent-based features
- Operations and business teams automating manual process
How it runs
On-site workshops
Delivered at your office anywhere in India — full-day or multi-day cohorts.
Remote cohorts
Live sessions for distributed teams, worldwide time zones.
Hands-on labs
Every module ends with working code, built against your stack where possible.
India — on-site nationwide, remote worldwide
Common questions
Who is this AI training for?
Engineering teams moving from AI demos to production systems, enterprises setting internal standards for AI use, and business teams automating manual process. Sessions are pitched to the room — developer cohorts go deeper into LangGraph and CrewAI, business cohorts spend more time on workflow design.
How much AI training have you actually delivered?
More than 120 corporate programmes across Agentic AI, LLMOps and mobile development, with over 1500 professionals trained and an average rating of 4.7 out of 5. That includes internal enablement for cross-functional engineering teams, GenAI sessions for enterprise clients, and community talks at Flutter Ahmedabad, GSDC WOW and AI meetups.
What tools and frameworks does the training cover?
LangGraph, LangChain, CrewAI, RAG and agentic RAG, MCP, the OpenAI API, prompt engineering, and LLMOps practice for deployment, monitoring and evaluation.
Do participants need prior AI experience?
No. Programmes are scoped to the cohort. Developer teams typically start further along; teams new to it start from first principles and still finish with something running.
Do you deliver training on-site?
Yes — on-site anywhere in India, and remotely for distributed teams worldwide.
Ready to scope a cohort?
Tell me the team size, their starting point and what you want them to be able to do afterwards. I’ll come back with a shape and a price.