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AutoPilot Hackathon

lumaHosted on Luma

Fetched 1 day ago

Saturday, May 16, 2026

to Sunday, May 17, 2026

•

1 day long

Artificial IntelligenceFintech

Event Type

in person

169

Participants

15

Est. Projects

AutoPilot is a national-level GenAI hackathon for builders who want to move beyond chatbots and create AI that actually executes work. Participants will build on Supervity Auto, starting with one operational AI Intern and progressing into a multi-agent, stateful AI Employee with a working AI Command Center. This is not a prompt-writing contest.This is a build challenge for AI that can reason, act, remember, and run workflows. Why Join AutoPilot? Build real AI Employees, not chatbot demosWork hands-on with multi-agent orchestrationSolve enterprise problems in Sales or MarketingCompete with serious AI builders from across IndiaGet early access to Supervity AutoWin cash prizes, swag, Auto credits, and hiring opportunities What You’ll Build Participants choose one of two tracks: Track 1: Sales — The Broken Sales Execution System Build AI that fixes CRM decay, lead qualification, meeting follow-ups, and sales admin.Track 2: Marketing — The Broken Growth Engine Build AI that connects trends, content, scheduling, campaign performance, and feedback loops. Workshop Live Builder Workshop: Get hands-on guidance with Supervity Auto, understand the challenge tracks, and learn how to build stronger submissions before hack day. May 07, 2026 | 7 pm onwards Selection Process & Timeline Round 1: The AI Intern Online Build Sprint9 May 2026 | 12:00 PM – 8:00 PM IST Teams build one working AI operator using Supervity Auto. Evaluation based on: Agent performanceBusiness usefulnessLogic and reasoningPlatform utilisation Finalists announced: 12/13 May 2026 2. Round 2: The AI Employee Offline Grand Finale — Mumbai 16–17 May 2026 Shortlisted teams build a multi-agent AI Employee with: Minimum 5 agentsStateful memoryMulti-agent orchestrationFunctional UI/dashboardWorking demo and live pitch Auto Launch 18 May 2026 Winning builds may be showcased as part of the official Auto launch. Event Details Mode: Round 1 online, Round 2 offlineFinale Location: Supervity Mumbai OfficeRegistration Fee: FreeFinalist Capacity: ~50 participantsTeam Size: 1-2Platform: Supervity Auto Rewards & Perks Winner Rewards 🎁 50k+ in Prizes👕 Winners AI Employees Get Featured in Supervity Auto Marketplace ⚡ Networking Opportunities🚀 Exclusive Access to Auto Platform on release day💼 Winners get direct entry into Supervity's FDE training Academy Judging Criteria Projects will be evaluated on: Technical implementationMulti-agent architectureReal-world usefulnessUI/dashboard qualityReasoning and orchestrationPitch clarity Execution matters more than ideas. WhatsApp Group Once you register, you will receive an email with a whatsapp link. Please join the group for updates and notification. It is mandatory. Note: Participants shortlisted for the Mumbai finale will need to arrange and cover their own travel expenses.

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