#POSSIBILITIES Hackathon 2022

4816 Registered Allowed team size: 1 - 5

Winners are announced.

Approach Submission
starts on:
Apr 14, 2022, 12:30 PM
ends on:
May 08, 2022, 06:25 PM



Watch the finale below!


ElasticRun brings to you the #POSSIBILITIES Hackathon 2022, Powered by Microsoft!

Kirana stores are a key conduit of  consumption in India. We find them on every nook and corner. Out of total 12 mn stores across the country, 10 mn stores lie in rural areas. These 10 mn rural stores remain underserviced by traditional distribution networks of CPG/FMCG brands because they are too far, too less in number and their demand is too less to fulfill. 

ElasticRun technology is changing this scenario by enabling a direct reach to these rural stores through crowdsourcing and aggregation. ElasticRun is empowering rural entrepreneurs with better earning opportunities and it is also enriching lives for rural consumers by making multiple life enhancing products available to them. It is a network of opportunities. It is a network of possibilities.


The Hackathon is divided into 3 phases:

Phase 1: Approach Submission (Submit on this page)

Participants are required to form teams with 1-5 members, and submit the approach that they will use to solve the problem statement of their choice given in the themes section. It is mandatory to submit your approach in this specific format - click here to download the format. You need to submit a PPT in the approach format. If you do not submit your approach in the given format you will not be eligible.

Phase 2: Prototype Submission (Another link will be provided)

Shortlisted teams from the approach submission phase will be promoted to the Protoytpe Submission phase. In this phase, team leaders will be sent an invite to solve the problem statement that they had opted for in the approach phase. Teams need to work together on their local systems, but only team leaders will received the invite to make submit on the platform. This round will take place in a separate link/ page which will be shared to team leaders of shortlisted teams when the time comes.

Phase 3: Onsite Presentation Round

Shortlisted participants from the prototype submission round will be invited to participate in the onsite final presentation round to be held in Pune! The address of the ElasticRun Pune office is ElasticRun, 2nd Floor, Wonder Cars Arena Bldg, Pimple Saudagar, Pune - 411027. Click here for the location.

Note: ElasticRun will not reimburse or compensate for any costs associated with travel or lodging for the event.


It is mandatory to submit your approach in this specific format - click here to download the format. You need to submit a PPT in the approach format.

We will be doing the evaluations in 2 batches:

  1. Batch 1 - All approaches submitted by 2nd May
  2. Batch 2 - All approaches submitted by 8th May
Problem 1 - Suggest relevant products for a store

Problem Description

Develop a ML system to determine relevant products for a store based on its past transaction history. These suggestions can be used in multiple sales channels to the store like self ordering app, sales executive PDA or by a calling agent to ensure that store is not missing out on any of these relevant products.

Train a model on the given dataset to predict each customer's next order

Participants may make the following assumptions

  • Every store has max 1 transaction per day which may contain multiple products
  • All stores served from the same fulfillment center are exposed to the same set of products. Hence, participants may create separate models per fulfillment center

Evaluation Criteria - 

  • We will evaluate based on the recall score on test dataset
  • Recall score will be calculated as - count of items which were predicted and bought / count of items which were bought
  • Achieving a higher recall score indicates better performance

Submit your approach on how you will solve this problem. The full problem statement will be revealed if you are shortlisted for the next phase.

Problem 2 - Profile a store based on it’s photo

Problem Description

Given a store’s image, try to predict:

  • Category of products store sells (bonus points if we can identify the exact brand and product as well)
  • Whether the store is small, medium or large in size


Computer vision can help better understand the store. Knowing the size of the store and the kind of products it sells would feed back into the personalisation engine for customized products and offers to the store. 

Stores exist in different sizes and shapes in India and hence it makes this image processing and analysis problem more interesting.

Participants may make the following assumptions

  • Use the available information in the image to identify product categories. Broad categories we are looking for are Chips, Biscuits, Snacks (other than chips), Masala, Beverages, Cosmetics, Noodles, Soaps.
  • Participants are free to add more categories as required. (e.g Bakery Items)
  • Participants are free to drill down into categories. e.g. Beverages can be broken down into Beverages - Tea, Beverages - Coffee
  • Exact dimensions of the store are not required. The mechanism of store classification needs to be explained in the approach
  • Any appropriate annotation tool can be used
  • A confidence score of 50% or above is acceptable, unless explained otherwise
  • Participants need to provide precision, recall and MaP at various levels along with prediction outputs

Evaluation Criteria

  • For category identification
    • Percentage of categories accurately identified overall with confidence score of over 50% 
    • New categories or sub-categories added and detected with confidence score of over 50%
    • Precision, recall, MaP overall and per class
    • Ability to detect in low-quality / blurred images
    • Choice of algorithm
  • For store identification
    • Approach used for estimating store size
    • Accuracy of classification based on precision, recall, MaP overall and per class

Submit your approach on how you will solve this problem. The full problem statement will be revealed if you are shortlisted for the next phase.

Problem 3 - Floor Planning & Tagging Utility

Floor design and SKU storage is a standard problem statement for any warehouse. For micro warehouses, a cost efficient and simple solution needs to be devised which can be used on laptop and mobile devices seamlessly, with below objectives.

A station manager of a warehouse should be able to upload a warehouse floor plan (2D) and sketch the storage areas per category (biscuits, soaps, shampoos, chips etc.) and tag those areas with category names.

  • A simple floor mapping and tagging solution using javascript which can allow floor managers to custom mark storage areas for a warehouse floor and save the output in the form of a JSON document.
  • Given the SKU dimensions, highlight the area's amount of SKU units which can be stacked over (you can assume a safe stacking height of say 3ft).
  • Given an input invoice containing line items of SKUs and quantity, the utility should also be able to overlay a heatmap on the demarcated floor layout for the station manager highlighting different sized bubbles(based on qty of SKU in invoice) on demarcated areas.

A sample floor with tagged areas and highlighted heat map can be visualized as under -

Submit your approach on how you will solve this problem. The full problem statement will be revealed if you are shortlisted for the next phase.

Prizes INR 2,25,000 in prizes

Main Prizes
INR 1,00,000
1st Runner Up
INR 75,000
2nd Runner Up
INR 50,000
Special Prizes
Special Mention (2)

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