Sunbird AI Assistant
  • Overview
  • Functional Overview
    • The Problem
    • The Solution
    • Use Cases
      • e-Jaadui Pitara
    • Capabilities
  • Technical Overview
    • Architecture
    • Technology Stack
  • Get Started with AI Assistant
    • Key Steps to role out an AI Assistant Solution
    • Pre-requisites
    • Installation
    • Data Ingestion Process
    • Configuration
    • APIs
    • Bot Creation 101
  • Components
    • Sakhi API Service
      • Environment Variables
      • Pluggability of LLM Chat Model
      • Pluggability of Cloud Storage
      • Pluggability of Transaltion service
      • Pluggability of Vector Store
  • Release Notes
    • Release Convention
    • 3.0.0 (Latest)
    • 2.0.0
    • 1.0.0
  • Roadmap
  • Contribution Guide
  • FAQs
  • Knowledge Base
    • Best Practices
    • Indexing CSV Data
  • Contact us
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Overview

NextFunctional Overview

Last updated 11 months ago

Sunbird AI Assistant enables building Chat Bot based solutions powered by GenAI, that can provide easy access to timely, relevant and contextual information and suggestions to user queries. As part of Sunbird, it is a Digital Public Good (DPG) designed based on micro-services architecture and open for anyone to use.

The AI Assistant provides ability to understand and respond to queries in natural language (can support multiple languages). It analyses the overall context instead of just searching for exact keywords, leading to more precise and contextual responses.

The AI Assistant differs from generic AI chat bots like ChatGPT by its ability to train the bots on specific set of contents based on which the responses are provided. This would make the responses trustworthy and a lot more relevant to the use cases being implemented.

As a DPG, it enables the following:

  1. By being platform independent, DPG based solutions bring in the value of eliminating vendor or product lock-in. This is very important for long term sustainability of the solution.

  2. Provides more choices for implementation and hence can enable optimized solutions for a given scenario.

  3. Through open specifications and standards, it enables interoperability. This helps in easy stitching together of multiple solutions creating multiplier value.

  4. Open license and an open ecosystem around it, enables easy evolvability. The DPG can adapt and evolve over time, allowing for continuous updates. It would invite others to join and build solutions, thereby enhancing its value proposition and ensuring ongoing relevance and usefulness.

  5. Apart from software, it enables creating a common knowledge base as part of the DPG in terms of guidelines, best practices and processes in rolling out solutions.

  6. The open source software also reduces initial time and cost of creating solutions.

A national scale adoption of Sunbird AI Assistant is by NCERT.

e-Jaadui Pitara