Rakathon 2024

8949 Registered Allowed team size: 2 - 4
8949 Registered Allowed team size: 2 - 4

Winners are announced.

Idea Phase
Online
starts on:
Jul 10, 2024, 01:30 PM UTC (UTC)
ends on:
Aug 04, 2024, 06:29 PM UTC (UTC)
Grand Finale
starts on:
Aug 30, 2024, 05:30 AM UTC (UTC)
ends on:
Aug 31, 2024, 07:30 AM UTC (UTC)

Winners

Evaluation Criteria

1. Novelty/Originality: This refers to the degree to which the idea or product being proposed is new or unique. The review committee may consider whether the proposed idea has been done before, and if so, how the proposed idea differs or improves upon existing ideas.

2. Practicality/Feasibility: This criterion assesses whether the proposed idea is realistic and achievable. The review committee may consider factors such as the availability of resources, time, and expertise required to implement the idea and potential obstacles or risks that may impede its implementation.

3. Usefulness/Desirability: This refers to the degree to which the proposed idea addresses a real need or problem. The review committee may evaluate how the proposed idea aligns with current market trends or demands and the potential impact it may have on the target audience.

4. Scalability/Biz Viability: This criterion assesses the potential for the proposed idea to generate revenue and be financially sustainable. The review committee may consider factors such as the target market, competitive landscape, pricing strategy, and potential profitability of the proposed idea.

5.Platformisation: This criterion evaluates the potential for the proposed idea to be expanded and adapted over time. The review committee may consider factors such as the ease of replicating or scaling the idea, the potential for partnerships or collaborations, and the potential for the idea to be developed into a platform or ecosystem that supports other products or services.

6. Privacy Handling: Depth and cognizance towards handling privacy and governance of data aspects in the usage of GenAI. Sources of data, pedigree of the data, best practices followed in the usage, patterns of using the data that is output from the solution, storage nuances, etc.

7. Choice of dataset/opensource used: and what kind of value add the team has done whilst bootstrapping the aforementioned aspects 

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