Hey AMD Developers community,
I’m excited to share my hackathon project for AMD Developer Hackathon ACT II, Track 3: Unicorn / Open Innovation.
NexusOps AI is an enterprise AI operations platform that turns complex business requests and uploaded documents into auditable multi-agent workflows, executive-ready reports, and exportable deliverables.
Most enterprise teams do not just need a chatbot response. They need structured planning, document context, visible workflow steps, reviewable decisions, and reports that can be shared with managers, engineers, security teams, or stakeholders.
That is what NexusOps AI focuses on.
Core workflow:
1. User enters an enterprise operations request
2. User can attach PDF, DOCX, TXT, or Markdown documents
3. Four agents handle the task:
-
Planner Agent
-
Research Agent
-
Executor Agent
-
Reviewer Agent
4. The system generates a final operations report
5. The user can inspect the audit trace
6. The report can be exported as Markdown, PDF, or DOCX
Real-world use cases:
- Cloud migration readiness reviews
- Incident response reports
- Compliance preparation
- DevOps/SRE planning
- Executive technical summaries
- Internal operations documentation
- Consultant-style business/technical reports
Why it matters:
NexusOps AI can help teams reduce manual planning, analysis, review, and reporting time by turning messy requests and scattered documents into structured, reviewable outputs.
AMD / AI stack:
- AMD Developer Cloud positioning
- AMD ROCm target
- Gemma / Fireworks AI readiness
- FastAPI backend
- React/Vite dashboard
- Docker-ready architecture
- Audit trace and export pipeline
This is still an MVP, but the goal is clear: build an enterprise AI command center where businesses can inspect, trust, and ship AI-assisted operations work.
Project page:
https://lablab.ai/ai-hackathons/amd-developer-hackathon-act-ii/traceloop-ai/nexusops-ai
GitHub:
I’d really appreciate feedback from the AMD Developers community, especially around AMD deployment, Gemma inference, enterprise use cases, and how to make this more production-ready.