TOPIC 07 : AI-Enhanced Dynamic White-Label Configuration and Allocation Platform PFE

Objective & Expected Deliverables

• Build a POC white-label multi-tenant platform that can be configured without code changes or redeploys.
• Deliver an admin dashboard enabling theme/flow/config definition, real-time preview/testing and instant deployment via backend APIs.
• Integrate an AI-assisted module (TensorFlow.js) to analyze risk and recommend allocation models; demonstrate allocation recommendation flows.

Technical Stack & Tools

• Frontend core: React (TypeScript), Redux Toolkit, RTK Query / React Query, React Flow; UI & forms: Tailwind CSS / Material UI, Formik + Yup.
• AI (optional): TensorFlow.js for allocation recommendations and client-side risk assessment.
• Backend & persistence: Spring Boot (Java), Spring Data JPA/Hibernate, MySQL, JSON Schema Validation, JWT-based auth.
• Platform & DevOps: Docker, Azure Cloud, Bitbucket Pipelines / TeamCity (CI/CD), Cloud Blob Storage.

Intern Responsibilities & Tasks

• Implement the admin dashboard features: multi-tenant configuration UI, preview/test environment, and connectors to backend deployment APIs.
• Develop the backend APIs to store tenant configurations, validate JSON schemas, and trigger instant rollout without redeploys.
• Prototype and integrate a TensorFlow.js module that analyzes risk profiles and suggests allocation models; expose recommendations to the admin UI.
• Ensure multi-tenant separation (branding, onboarding flows, allocation logic) and create examples of configurable tenants.
• Add CI/CD integration and storage handling (blob storage) for assets; write tests and documentation for deployment and onboarding flows.

Expected Outcomes & Evaluation

• Deliver a working POC demonstrating self-service onboarding that reduces developer intervention and shortens onboarding time.
• Provide a recorded demo or live walkthrough showing: tenant creation, theme/flow configuration, real-time preview, allocation recommendation, and instant rollout.
• Submit source code, deployment scripts (Docker/Azure), test cases, JSON schemas, and a concise technical report describing architecture and scalability considerations.

Practical Information & Application

• Pre-employment Internship Duration: 6 months (listed as 4-6 months for the internship posting).
• Number of interns: 1; Paid Internship.
• To apply, send your application to the internship email: stages@binitns.com.