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Typography

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Moodboard

Ditch the Payday Wait

Your Earned Wages, Anytime, Anywhere

Challenge:

  • Building a secure and user-friendly digital platform: Valyu.ai needed to create a completely digital experience for e-KYC and salary access, ensuring both security and ease of use.
  • Balancing transparency with fees: While avoiding hidden fees and interest charges, Valyu.ai needed to implement a sustainable business model with clear, minimal withdrawal fees.
  • Gaining trust with employers: Providing salary advances without credit checks or background checks could be a hurdle in convincing corporations to partner with Valyu.ai.

Impact

  • Financial well-being for Indian workforce: Valyu.ai empowered over one million Indian workers with instant access to earned wages, potentially reducing financial stress and improving overall well-being.
  • Addressing liquidity crunch during pandemic: Their partnership with HR providers and corporations offered a crucial solution to service workers facing financial hardship during the COVID-19 pandemic.
  • Promoting financial inclusion: By simplifying access to earned wages, Valyu.ai might be contributing to greater financial inclusion for underbanked or underserved communities.

Valyu.ai's Tech Stack Breakdown:

Valyu.ai is a tech-driven company that leverages a robust tech stack to deliver a fully automated and personalized user experience. The focus on AI, ML, and cutting-edge cloud infrastructure positions them well for future advancements.

  • AI and Machine Learning (ML) Algorithms at the Core:
    • Risk Management: Continuously monitoring customer risk profiles with an ML-based rules engine.
    • Credit Approval: Self-learning credit approval engines update scorecards for better decision-making.
    • Personalized Products: Digital Product Design Lab uses AI to tailor product configurations to individual customer needs.

    Cutting-Edge Technology Infrastructure:

    • Cloud-first approach with serverless and asynchronous architecture for scalability and flexibility.
    • An early adopter of AWS TimeSeries DB for efficient time-based data storage and retrieval.
  • Programming Languages and Frameworks:
    • Middleware and Backend: NodeJS and GoLang
    • AI/ML and Rules Engines: R, Python, TensorFlow, Drools, and H2O
    • Application and Presentation Layer: Kotlin, Swift, and ReactJS

    Cloud Services and DevOps:

    • Utilize both Google Cloud Platform (GCP) and Amazon Web Services (AWS) for cloud infrastructure.
    • Leverage Github and Github runners for continuous integration/continuous delivery/continuous deployment (CI/CD/CR) pipelines.