RIO Co‑lab built the RIO Co‑lab, a multi‑agent risk‑register analysis and visualisation solution that applies specialist AI agents to identify themes, assess data quality, summarise change, and surface actionable insights across project and portfolio risk registers.

CutVac Risk Cleaner implemented a Python‑based risk‑register processing and feedback pipeline that cleans, validates and analyses risk and mitigation data, then generates automated, insight‑driven email prompts to drive corrective action.

Risk Review Regulator designed a set of agentic AI personas to automatically review risk registers, analyse data quality and exposure, and drive action through targeted, human‑centred email nudges. The solution demonstrates a closed‑loop risk‑management cycle spanning project, portfolio, and enterprise views.

F-Code Recruitment portal for managing candidate challenges, assignment submissions, presentation scheduling, and result tracking.

Risky presented a concept prototype focused on applying agentic AI to proactively interrogate risk registers and surface actionable insights for regulators and delivery teams, emphasising clarity of narrative and decision support.

En este desafio nos enfocamos en crear un e-commerce llamado alura geek en el cual se vende productos, ademas se usara una pequeña base de datos en donde realizaremos peticiones para que el e-commerce sea accesible como administrados y asi cambiar o eliminar cada producto.