Airton Justino de Oliveira Junior@airtonjustino
3
Events attended
2
Submissions made
Brazil
3+ years of experience
About me
I’m a CRM and AI Solutions Specialist from Brazil, connecting business needs with practical technology. My background spans Salesforce, business analysis, process automation, and integrations. I’m building JJ AI Platform to orchestrate AI agents and workflows, with governance, observability, and cost tracking, using Python, FastAPI, PostgreSQL, React, and TypeScript. Currently pursuing an MBA in Artificial Intelligence for Business, I’m interested in reliable multi-agent systems and AI that delivers measurable value. I enjoy turning complex problems into working solutions and collaborating with people who like to build, test, and learn.
🤓 Latest Submissions
Elo Functional Intelligence
Elo Functional Intelligence is a human-centered AI platform designed to support pediatric occupational therapists in transforming session observations into structured, traceable functional information and family-friendly communication. **The Problem** Occupational therapists must document meaningful observations while remaining focused on the child. Information about participation, independence, assistance, attention, and task transitions can become fragmented across notes and reports, making it difficult to communicate clearly with families. **Our Solution** Elo provides an integrated workflow for organizing therapy sessions, reviewing observations, exploring functional indicators, and generating evidence-linked family reports. The platform includes operational dashboards, Functional Progress, Functional Intelligence, and AI Governance views. Each functional statement can be traced to supporting session evidence. **AMD Integration** Elo integrates AMD Token Factory infrastructure to support AI-assisted report generation. The implementation emphasizes controlled generation, traceability, and human review rather than autonomous clinical decision-making. **Human Oversight** A professional reviewer must explicitly approve generated family-report content. The system preserves review decisions and audit records, keeping clinical judgment with the human professional. **Working Demonstration** The prototype demonstrates an end-to-end workflow using synthetic pediatric occupational therapy data: reviewed session observations, functional dashboards, AI-assisted report generation, evidence references, and explicit human approval. **Our Vision** Make functional documentation more understandable, auditable, and useful for communication between occupational therapists and families, without replacing professional expertise. Elo is a functional prototype, not a validated medical device. No clinical effectiveness or longitudinal improvement is claimed.
18 Oct 2026
Gather — Built by a Dark Factory
Gather is a restaurant reservation platform created by an autonomous software factory for the Tablekeeper track of the WeAreDevelopers × BAND Dark Factory Hackathon. Instead of treating AI as a coding assistant, we designed a reusable three-seat factory: a Coordinator plans and delegates work, an Implementer builds the solution, and an independent Reviewer challenges the implementation before accepting it. The mandates are generic and reusable rather than Tablekeeper-specific. The factory progressed cumulatively through all four Tablekeeper stages. Review was not ceremonial: implementations were rejected when defects were discovered, corrected through additive commits, independently re-tested, and only then accepted. In the final stage, the Reviewer identified consistency problems beyond the public test suite and required additional correction cycles before final acceptance. The resulting application, Gather, provides a complete restaurant reservation experience with availability discovery, table-capacity management, combined seating, authenticated reservations, confirmation references, reservation lookup and cancellation. Underneath the interface, the system handles harder concerns including concurrency, idempotency, time zones, recurring reservations, policy evolution and atomic seating replanning. The final cumulative Stage 4 verification passed all official stage checks. Additional independent adversarial testing exercised optimizer behavior, rollback guarantees, stale-plan handling, concurrency, API behavior and browser flows. Most importantly, Gather is not simply a demonstration of what an AI model can code. It demonstrates a software factory in which autonomous agents coordinate, implement, review, reject, correct and ultimately ship working software.
6 Oct 2026
