Aventure Cloud AI Lab
The Aventure Cloud AI Lab is where we build and teach Agentic AI. It is the portfolio of what our Trainings on AI learners build toward.
Agentic AI Engineering — sample portfolio
The standard our Trainings on AI learners build toward: 42 public repositories, every project documented the same honest way — the problem, what was built, the tech, and the tests.
This portfolio is a synthetic, fictional sample built for training and demonstration. It is not client work and has not been deployed to production.
Sample projects
- Support Triage Agent — an agent that reads incoming support requests, classifies them, and drafts a first response.
- Policy Document Q&A — ask questions of a policy document and get grounded, cited answers.
- Invoice Processing Pipeline — extract, validate, and reconcile invoice data automatically.
- Research Assistant Agent — plan a research task, gather sources, and summarise findings.
- LLM Evaluation Harness — test sets, scoring, and guardrails for language-model outputs.
- Codebase Navigator — ask questions about a codebase and get answers with references to the code.
- Meeting Notes to Actions — turn meeting notes into clear actions and owners.
- Data Quality Agent — check datasets for completeness, consistency, and drift, and report issues.
- Guardrail Test Suite — adversarial prompts and safety checks for agent behaviour.
Agentic AI in the Lab
Agentic AI in the Lab — LLM application patterns, agent design (planning, tool use, memory, and multi-agent workflows), RAG systems, and evaluation & safety. The Lab is where the Forward Deployment Engineer path is practised: traditional software → intelligence layer → end to deployment.
How the Lab connects to Trainings
Learners in Trainings on AI build toward this standard: working, tested projects with an evaluation harness. Capstone projects are built to the portfolio standard, with full test suites.
Want to see the Lab, or learn to build agents like these? Email info@aventurecloud.net.