This task focuses on creating an AI-based onboarding assistant to streamline and automate the institution onboarding process for the Academic Bank of Credits (ABC) and NAD-DigiLocker ecosystem. The goal is to reduce manual intervention, improve accuracy, and ensure faster eligibility verification for institutions by intelligently guiding them through each step of the onboarding journey.

The onboarding advisor should use AI to pre-screen registrations, validate institutional data from authoritative databases (UGC, AICTE, NCVT, etc.), and dynamically generate contextual prompts to assess institutional readiness (e.g., data format used, ABC ID integration, digital certificate issuance).

By automating common checks and capturing readiness indicators early in the process, the system can help filter unqualified or duplicate registrations, assist new institutions with next steps, and reduce the load on human reviewers. This tool should support facial recognition or document scanning (UGC/Autonomy Letters), and auto-fetch data using AISHE codes to pre-fill institutional details.

• Develop an intelligent onboarding flow with:

  • AI-powered prompts that ask contextually relevant questions based on the user's profile or input (e.g., "Do you maintain data in CSV or XML?" or "Have you issued ABC IDs to your students?")

  • Pre-validation of institutional registration data using public databases (UGC, AICTE, NCVT, etc.) and AISHE code-based lookups.

  • Duplicate or invalid registration detection using NLP and pattern matching.

  • Facial recognition module or document scanning for verifying official documents (optional module).

• Integrate a lightweight chatbot or conversational UI to assist institutions in real-time.

• Provide real-time recommendations on steps needed to complete onboarding (e.g., "Digitize historical student records", "Generate ABC IDs").

• Log responses for audit and dashboard summarization.

A working onboarding advisor tool that:

• Screens institutions for eligibility using predefined checks and AI logic.

• Interacts with users using dynamic question trees to assess readiness.

• Validates institution metadata from authoritative sources using AISHE code or API integrations.

• Helps avoid duplicate registrations and incorrect submissions.

• Includes a simple front-end interface (CLI or Web-based) and back-end logic that can be deployed on NAD/ABC platforms.

• Comes with sample flows, test cases, README, and deployment guide.

Submit tool scripts via Git. Functional workflow in a staging environment + chatbot training data

https://openforge.gov.in/plugins/git/abc-collabwithgov/abc-onboarding-assistant

Organization Type: Government Publisher Name: Academic Bank of Credits (Digital India Corporation)