Bruno and OpenClaw
An orchestration layer that coordinates sources, memory, tasks, documents, flows and next steps so work can move with continuity.
ATIEMPPO Lab · Applied AI
Four projects showing how we build AI for real work.
These cases connect agents, sources, documents, data, memory, reports, automation and learning into a working table. They are live cases that explain a way of working with artificial intelligence.
The thesis
Start with the process, then choose the tool.
Each project answers a different question: how AI can execute, monitor dispersed logistics information, build a living editorial system and teach applied AI through real work.
Road updates
A specialized agent that monitors road signals, compares cuts and delivers an operational reading with sources and visible limits.
El Dato Logístico
An AI-supported editorial and knowledge system that monitors signals, organizes topics, prepares products and publishes living reports.
Profe Bruno
An applied learning initiative that helps people and teams connect AI with documents, data, decisions and repeatable work.
What connects them
Agents with roles, sources, memory, tools, limits and deliverables.
ProcessWe begin with information and decisions that repeat or need better context.
EvidenceSources and outputs remain visible so a person can review and continue.
ContinuityLearning, reports and memory help the work persist beyond one conversation.
PracticeThe case becomes useful when a team can connect it to its own task.