Filtering through endless, unverified real estate listings leaves property seekers confused about true commission rates and coverage zones. At the same time, qualified local brokers miss out on active leads because they lack a clear way to showcase their specific neighborhood expertise.

But with Fetch Agent, this mismatch disappears, as house hunters pinpoint active consultants right on regional maps, while smart sliders allow them to sort experts by flat fees or percentage rates before any contract begins. For professionals, built-in countdown timers highlight incoming invitations so hot leads never expire.

Shifting communication away from messy email threads into dedicated text channels accelerates the entire home-buying process. Clear dashboard tables keep track of contract lengths and client ratings, ensuring complete transparency and legal security for both sides of the transaction.

Brilliant product design! The UX layout solves a massive real estate pain point with clean data tables and smart map filters, while the shattered concrete mockups add an incredibly distinct, premium edge to the presentation. Love this! 🗺️✨

What it actually takes to build a multi-tenant edtech SaaS from scratch

Everyone wants to build a SaaS. Few people talk about what happens when 500+ schools hit your system at the same time, each expecting their data to be completely isolated.

I built EduPilotPro, an AI-powered school operating system serving schools across South Asia, the Middle East, and Africa. Here's what the "multi-tenant SaaS" part actually looked like:

Tenant isolation is the first real decision. Every school needs to feel like they own the platform. Their data, their config, their branding. But you're running one codebase, one database cluster, one deployment. We used PostgreSQL with row-level isolation on self-hosted Supabase. Each school gets its own logical boundary without the cost of spinning up separate infrastructure per tenant.

The 8:45 AM problem. Schools don't use software evenly throughout the day. At 8:45 AM, every teacher in every school marks attendance simultaneously. That's a traffic spike that would embarrass most startups. We used Redis + BullMQ to queue attendance writes and process them asynchronously, so the UI stays responsive even when thousands of classrooms hit the system at once.

AI agents, not AI features. We didn't bolt a chatbot onto a school ERP. We built 6 purpose-built AI agents: attendance, admissions, fees, communication, reporting, and scheduling. Each one handles a specific administrative function end-to-end. A teacher types "All students present except Ali who is sick and Ahmed who is 10 minutes late" and the attendance agent parses it, records it, and notifies parents. No forms. No checkboxes.

The stack: Next.js + React + TypeScript on the frontend. Node.js + self-hosted Supabase on the backend. PostgreSQL + Redis + BullMQ for data and queuing. Railway for cloud infrastructure.

What I'd tell any founder about to build multi-tenant SaaS:

Design your tenant model before you write a single feature. Retrofitting isolation is painful.

Assume your traffic will be spiky, not smooth. Queue everything you can.

If you're adding AI, make it do the whole job, not half of it. A half-automated workflow is worse than a manual one because now nobody knows who's responsible.

→ Full case study: EduPilotPro on Contra

Perfect