LLM application development
Python, model APIs, prompt engineering, tool calling and structured outputs.
AGENTIC AI · SKILLCLOUDLABS
AI & Agentic AI Labs
Build, test and orchestrate intelligent applications in ready-to-use environments.
Explore agent workflows, grounded retrieval, integration patterns and evaluation using a consistent learner setup.
LangChainLangGraphRAGMCPPythonVector databasesn8nLLM APIs
CAPABILITIES & LEARNING TRACKS
Built around real hands-on outcomes.
We can configure the following technology components based on the course outline, licensing, regional availability and desired cohort size.
LangChain & LangGraph
Stateful agents, routing, multi-agent workflows, checkpoints and human-in-the-loop patterns.
RAG & vector search
Document ingestion, chunking, embeddings, vector databases and grounded answers.
MCP integrations
MCP servers, enterprise tool interfaces, permissions and observability.
AI development tools
VS Code, Git, notebooks, CLI tools and integration with supported AI assistants.
Quality & monitoring
Evaluation datasets, prompt regression testing, tracing and latency analysis.
DESIGNED FOR YOUR COHORT
From brief to learner-ready.
Example engagement: Agentic AI bootcamp, RAG workshop or multi-agent engineering course. We align environments to the exercises, operating systems, learner access and schedule, then validate the setup before delivery.
01 Share the syllabus, dates and cohort count
02 Confirm tool versions, identities and licenses
03 Prepare and validate learner environments
04 Share access instructions and support plan
Need a lab tailored to your course?
Tell us the program scope, trainee count and required technology stack. We'll help plan a practical lab environment.