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Opus Hackathon

lumaHosted on Luma

Fetched 5 months ago

Sunday, February 15, 2026

to Sunday, February 15, 2026

Artificial IntelligenceOpen SourceInnovation

Event Type

in person

96

Participants

8

Est. Projects

Introduction to Opus Opus is an AI-native workflow builder developed by AppliedAI that converts plain-language prompts into executable workflows. It provides a visual canvas where users drag, connect, and configure nodes such as inputs and outputs, AI agents, human review steps, integrations, and decision logic. Workflows can be executed as jobs with full logs and traceability. Key capabilities include: Prompt-to-workflow generation from natural languageVisual canvas builder with no coding requiredAI Agent nodes for intelligent processingDecision nodes for conditional routingHuman Review checkpoints for validationOCR and text extraction for documentsExternal integrations and custom Python execution About the Hackathon This hackathon is a practical build session where participants work directly with Opus to design and execute automation workflows. After a short introduction and demonstration, teams will define use cases, construct workflows, and run them end-to-end. Participants are encouraged to explore workflow orchestration, agent coordination, decision routing, and human-in-the-loop validation to solve operational or analytical problems. Mentors will be available throughout the session for technical guidance. The event concludes with short presentations where teams showcase their workflows and discuss their approach. Prizes 1st prize - AED 3,0002nd prize - AED 2,0003rd prize - AED 1,000 Event Agenda 10:00 – 10:30 AMIntroduction to OpusChallenge revealQ&A10:30 AM – 6:00 PMHackathon Build Session6:00 – 7:00 PMJudging and selection of top 5 teams7:00 – 7:45 PMFinal presentationsTop teams present (5 minutes each)7:45 – 8:00 PMClosing remarks and felicitation Training Material Understanding the Platform & UILive Workflow DemonstrationDeveloper documentation Please review the training material prior to the event to maximize hands-on build time.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct