AI Platform Developer & Data Engineer
Hosted on UnstopFetched about 2 months ago
Tuesday, April 14, 2026
to Saturday, April 25, 2026
•
2 weeks long
Artificial IntelligenceData ScienceEdtech
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
online
67
Participants
6
Est. Projects
About the Project
The project focuses on addressing inefficiencies in Sales, Distribution, and Marketing (SDM), where fragmented execution and unstructured decision-making limit business outcomes. It is being developed as a structured, AI-enabled system through three stages: system design and frontend development to define user interaction and input flow, backend development to establish the core processing and data structure, and agentic AI orchestration to enable coordinated AI-driven support across SDM activities. The overall objective is to create a scalable framework that improves clarity, alignment, and decision-making without exposing underlying system logic.
About the Opportunity
We are organizing a national-level hackathon focused on AI-driven business intelligence and execution systems.
Participants will work on building AI-powered platforms and structured technical data rooms, solving real-world business problem statements using automation, machine learning, and intelligent workflows.
Role Objective
To design and develop a functional AI-enabled platform prototype along with a comprehensive technical data room, showcasing architecture, logic, and execution capability.
Key Responsibilities
AI Platform Development
Build a functional prototype (web/app-based) using AI integration
Design intelligent workflows based on problem statements
Develop systems capable of:
Input understanding (text-based or structured)
Output generation (insights, recommendations, or workflows)
Integrate AI APIs / models for automation and decision support
Technical Data Room Creation
Participants are required to build a complete technical data room, including:
Platform architecture (system design, workflows, logic)
AI model usage / integration approach
Tech stack documentation
Feature breakdown and modular structure
Scalability and future scope consideration
System Design & Logic Building
Create structured problem-to-solution frameworks
Define input-output pipelines
Develop logic for automation, scoring, or recommendations
Focus on efficiency, usability, and clarity of output
Prototype & Demonstration
Build a working or semi-working prototype
Present:
Platform functionality
AI integration
Use-case demonstration
Deliverables
Functional / semi-functional AI-based platform prototype
Technical Data Room (well-structured and documented)
System architecture + workflow diagrams
Skills Required
Core Technical Skills
AI/ML fundamentals (must-have)
Python / JavaScript / Node.js / React (any stack)
API integration & backend logic building
Basic understanding of system design
AI & Advanced Skills (Preferred)
Prompt engineering
Workflow automation tools
Data processing & structuring
Experience with AI-based projects (strong preference)
Additional Skills
Problem-solving and analytical thinking
Ability to convert ideas into structured systems
Documentation and presentation skills
Eligibility
Students from Engineering / Tech / Data / AI backgrounds
Individuals who have worked on AI-based projects / prototypes
Strong interest in building AI-powered products
What You Will Gain
Hands-on experience in building AI-powered platforms
Exposure to real-world problem-solving using AI
Opportunity to showcase technical and product-building skills
Certificate of Participation
Performance-based recognition
Top performers may receive Job Opportunity (PPO).
SDM Agentic AI Hackathon - 3 Stage Track
This hackathon challenges participants to design and build a one-stop Sales, Distribution, and Marketing Agentic AI solution that includes concept, intelligence models, and business feasibility.
Stage 1 — 1 DayStage 2 — 3 DaysStage 3 — 2 Days
Total = 6 Days
Stage 1 - Ideation & Concept Design
Objective
Design the SDM Agentic AI platform architecture
Participants Must Define
SDM problem statement
One-stop SDM solution concept
Sales Distribution Marketing integration logic
Agentic AI orchestration structure
Input → Processing → Output flow
Decision to execution mapping
Output
SDM platform concept
AI orchestration logic
System architecture flow
This stage builds the platform foundation.
Stage 2 - Prototype Development
Objective
Develop 15 Agentic AI models for SDM activities
Participants must create:
Sales (5 Models)
Lead generation AI
Sales forecasting AI
Pricing decision AI
Pipeline optimization AI
Conversion improvement AI
Distribution (5 Models)
Territory mapping AI
Dealer expansion AI
Inventory optimization AI
Distributor performance AI
Channel optimization AI
Marketing (5 Models)
Campaign planning AI
Demand generation AI
Market research AI
Promotion optimization AI
Branding strategy AI
Output
15 Agentic AI SDM Models
This stage builds the intelligence layer.
Stage 3 - Need, Budget & ROI Analyzer
Objective
Build business justification and decision layer
Participants must create:
Need Analyzer
Business problem identification
Current inefficiency measurement
Gap analysis
Opportunity size
Budget Calculator
Implementation cost
Resource cost
Technology cost
Deployment cost
ROI Calculator
Revenue impact
Cost savings
Payback period
ROI multiple
Output
Complete feasibility & investment decision model
This stage builds the business validation layer.
Final Hackathon Outcome
By end of Stage 3 participants create:
SDM Agentic AI Platform Concept15 AI Decision ModelsAI Orchestration LogicNeed AnalyzerBudget CalculatorROI EngineExecution Flow
These results in a complete SDM decision-to-execution AI system.
CHALLENGE MATRIX (CORE EVALUATION ENGINE)
Dimension
Benchmark (Quantified)
Quality Standard
Triggering Conditions (Failure)
Rewards
AI System Architecture
15/15 agents implemented
Modular, scalable, orchestrated
Missing agents / weak logic
Shortlist for AI/Product roles
Workflow Intelligence
100% mapped pipeline
Autonomous decision loops
Linear/no intelligence flow
System Architect Recognition
Financial Model
ROI ≥ 2x, Payback ≤ 18 months
Investment-grade modeling
Unrealistic assumptions
IB/Consulting fast-track
Technical Documentation
100% coverage
CTO + Investor ready
Missing clarity/logic gaps
Portfolio-grade certification
Market Validation
≥ 3 industries tested
Execution-backed strategy
Generic ideas
Jury distinction
Prototype
Functional or semi-functional
Clean UX + logical flow
Broken demo
Product showcase visibility
Data Structuring
≥95% structured pipelines
Scalable architecture
Unstructured inputs
Tech excellence badge
Compliance
0 violations
Full NDA adherence
Any breach
Immediate elimination
EVALUATION FRAMEWORK
Quantitative (80%)
AI Model Development → 20%
System Architecture Efficiency → 15%
Financial Justification (ROI, Cost) → 15%
Technical Documentation → 10%
Prototype Functionality → 10%
Market Validation → 10%
Qualitative (20%)
Strategic Thinking → 10%
Communication & Storytelling → 10