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The University Admin CRM is a centralized administrative dashboard designed to help educational institutions manage students, leads, and operational data efficiently.
The platform provides role-based access control, analytics dashboards, and structured data management to streamline university administrative workflows. It enables administrators to track leads, manage student information, and gain insights through a unified system.
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Thank you so much for Margadarsi Infra for this opportunity🎉
Intelliflow build entire Digital platform for Margadarsi Infra #realestate business.
Where Intelliflow Built the
Public website
Lead Management system
Dedicated Channel partner portal
#websitedesign #websitedevelopment #webapplication #softwaredevelopment
#CRMdevelopment
Its a wow design!
AI Governance Dashboard | Control AI Usage. Ensure Compliance.
AI is becoming part of every organization, but managing how teams use AI tools is becoming a serious challenge.
I designed this AI Governance Dashboard to bring policy management, compliance monitoring, AI application usage, user activity, and governance analytics into one centralized platform.
The goal was to keep a complex enterprise product simple, clear, and actionable through:
• AI Policy Management
• Compliance Monitoring
• AI App Usage Analytics
• User & Access Management
• Governance Status
• Policy Activity
• Compliance Reporting
The interface uses a clean SaaS design system with clear hierarchy, data visualization, subtle gradients, and focused interactions.
Designed in Figma.
If you're building an AI SaaS, enterprise dashboard, or web application, feel free to connect or message me.
The hierarchy is doing the hard work here—policy health, app usage, and governance status read as one calm operational story instead of a wall of enterprise data. The focused sidebar and restrained gradients keep the dashboard actionable without making compliance feel heavy.
just shipped the core of Skillship — an AI-powered LMS built for schools.
One platform, many schools, and one rule that shaped every decision: School A must never see School B's data. Tenant-scoped models, filtered querysets at the base class, UUIDs everywhere.
Four AI features live:
— Career Pilot: personalised career paths for students
— Question generator: chapter PDF in, board-aligned MCQs out
— Adaptive quizzes: difficulty follows actual performance
— Semantic search: teachers ask in plain English, pgvector finds the material
Django + DRF for the LMS core, a separate FastAPI service for all AI work (Gemini + a pgvector RAG pipeline), Next.js 14 on the front. Django brokers every AI call — the AI layer never touches the browser.
The hard part wasn't the AI. It was making multi-tenancy boring enough that no future dev can leak a school's data by accident.
Open for new work — full-stack builds, AI integrations, RAG pipelines, multi-tenant SaaS. Send me a project.
The tenant boundary is where I'd put the first failure test. I'd try to make a user from one school retrieve another school's record before I trusted any of the AI features.