Korosuke: A Hardware Device for Centralized Organizational Information Access

09 Oct 2024

Korosuke is an ambitious project aimed at developing a hardware device that serves as the central access point for all organizational data. This solution is designed to offer fast, secure, and localized data retrieval powered by AI and machine learning models. The device’s primary purpose is to enhance efficiency within organizations by making information retrieval instantaneous and cost-effective, without relying on cloud services.

Korosuke

The Problem Statement

Modern organizations often face significant challenges when it comes to managing and accessing vast amounts of internal data. Whether it’s retrieving internal documents, employee records, or customer data, the time spent searching and handling this information is substantial. Moreover, small to medium-sized businesses struggle with the high costs associated with deploying machine learning models via cloud-based services.

Key Problems Addressed by Korosuke:

  1. Cloud Dependency: Relying on cloud services for deploying machine learning models results in significant operational costs, making it less feasible for smaller organizations.
  2. Data Security: Sensitive organizational data stored and processed on the cloud is more vulnerable to breaches, increasing the risk for organizations handling critical information.
  3. Latency in Data Retrieval: Cloud services often experience latency in delivering real-time data, which can affect decision-making and operational efficiency.

The Korosuke Solution

Korosuke addresses these problems by providing a hardware solution that processes and stores data locally, ensuring real-time access, enhanced security, and lower operational costs. The device will host machine learning models trained specifically on closed organizational data, making it a highly secure and efficient tool for internal information management.

Why Build a Hardware Device?

Building a hardware solution rather than relying solely on cloud services comes with several benefits:

  1. Cost Reduction: Running machine learning models locally on Korosuke eliminates recurring cloud costs, such as API usage fees, and reduces the expenses associated with data transfer and storage.
  2. Data Security: Since data is stored and processed on-premises, the risk of data breaches is significantly minimized, offering enhanced compliance with data protection regulations.
  3. Instant Data Access: Local data processing removes network latency, making information retrieval and model responses immediate—crucial for real-time decisions and interactions.

Korosuke Design
Image: First Conceptual design of Korosuke

Key Features of Korosuke

Unlike traditional data management systems or isolated machine learning models, Korosuke is designed to be a complete platform that any organization can easily integrate. Here are the standout features:

  1. Centralized Data Access: The device will act as the single point of access for all organizational data, allowing employees to retrieve information from various internal sources effortlessly.
  2. AI-Driven Interactions: Korosuke incorporates a friendly AI personality, making interactions intuitive and engaging for users.
  3. User-Friendly Interface: An intuitive, user-friendly interface ensures that even employees with minimal technical knowledge can easily navigate and retrieve information.
  4. Secure Data Requests: While the device processes data locally, users will be able to send requested information to their mailbox or designated storage locations for easy access.
  5. Audit Logs: Every action and access request will be recorded in detailed audit logs, ensuring transparency and compliance with organizational policies.
  6. Update Management: Korosuke will feature an automated system for seamless updates and version rollbacks, ensuring the device stays up to date without disrupting operations.

Major Milestones

Hardware Design

The initial phase involved designing the hardware components of Korosuke. We selected a microprocessor capable of running machine learning models efficiently while ensuring that the device remained compact and cost-effective.

Model Training

One of the key challenges was to train a model that could operate locally on the device while remaining highly efficient. We fine-tuned a smaller machine learning model that could handle various organizational data types, including documents, employee records, customer feedback, and more.

UI/UX Development

To make the device accessible to non-technical users, we focused on building a highly intuitive and responsive UI. Users can interact with the device via a simple interface, retrieving data or sending it to designated locations like email with just a few clicks.

Ideal Scenario Components

For Korosuke to function at its best, we have outlined a few ideal components:

  1. Data Segregation and Formatting: Using web-scraping methods and large PDF rendering capabilities, Korosuke will efficiently format the retrieved data to suit the model’s needs.
  2. Model Selection and Training: The model should be small, efficient, and capable of delivering real-time results.
  3. Microprocessor Setup: The setup and configuration of the microprocessor are critical to ensuring Korosuke’s smooth and fast operations.
  4. Internet Connectivity for Updates: While the device processes data locally, it will support internet connectivity for system updates and information sharing.
  5. Audit and Log Management: Korosuke will maintain comprehensive logs for every interaction, ensuring accountability and transparency.

The Team Behind Korosuke

Korosuke is being developed by a dedicated team, each contributing their unique skills to bring this ambitious project to life:

  • Sachin: Machine learning expert responsible for the model’s fine-tuning and training.
  • Giridhar: Lead developer for the UI/UX and overall software integration.
  • Prakashita: Hardware engineer responsible for the design and setup of the device’s microprocessor.
  • Sushil: Lead backend engineer and project coordinator, overseeing the device’s architecture and integration.

The Future of Korosuke

Our goal is to file a patent for Korosuke, securing its innovative approach to localized machine learning and data access. We believe Korosuke has the potential to revolutionize the way organizations manage internal data by offering a cost-effective, secure, and user-friendly alternative to cloud-based solutions.

Upcoming Features

  • Mobile Application: In the future, we aim to expand Korosuke’s functionalities to mobile devices, ensuring seamless data access on the go.
  • Model Optimization: We continue to optimize the model to handle more complex datasets while reducing computational demands.

Korosuke is set to change how businesses handle data. By providing a local, secure, and AI-driven solution, we are not only reducing costs but also enhancing productivity and security within organizations.

If you’re interested in learning more or contributing to Korosuke, check out the Korosuke GitHub repository for the latest updates.

Stay tuned for future developments as we bring Korosuke to life!

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