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Thomas
Thomas

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Nigeria Rental Assistant — Conversational Housing Guide

What I Built

I built a conversational AI agent that helps people find rental apartments in Nigeria while avoiding common real-estate pitfalls.

Renting in Nigeria isn’t just about price; tenants often deal with:

  • Hidden costs (agency fees, legal fees, caution fees)
  • Unreliable infrastructure (power, water, road quality)
  • Misleading listings that don’t reflect reality

This agent acts like a street-smart local guide.

Instead of just listing apartments, it answers questions like:

  • “Is ₦800k realistic for a 2-bedroom in Lekki?”
  • “What extra fees should I expect?”
  • “Is this area good if I don’t have a car?”

The experience is friendly, conversational, and practical, designed to feel like asking a knowledgeable friend — not browsing a cold property website.


Demo

🔗 Live demo: Link

The demo shows:

  • Natural back-and-forth conversation
  • Area-specific rental guidance
  • Cost breakdowns beyond rent
  • Context-aware follow-up questions

How I Used Algolia Agent Studio

I used Algolia Agent Studio to power the agent’s retrieval-augmented conversations.

Indexed Data

I created a custom index containing:

  • Rental listings across Nigerian cities
  • Location metadata (state, city, neighborhood)
  • Rent ranges and upfront fees
  • Infrastructure notes (power, water, road access)

This data was indexed with searchable attributes and filters, enabling the agent to:

  • retrieve relevant locations,
  • present realistic price ranges,
  • and provide contextual housing details.

Retrieval-Enhanced Dialogue

Instead of relying on generic LLM responses, the agent:

  • retrieves relevant listings and area data from Algolia,
  • grounds its answers in real indexed information,
  • and responds conversationally using that context.

Prompt Engineering

I used targeted system instructions to ensure the agent:

  • stays Nigeria-specific,
  • avoids hallucinating prices or locations,
  • explains why a listing may or may not be realistic,
  • and highlights hidden costs and infrastructure realities.

Algolia handles what to retrieve; the agent focuses on how to explain it clearly to a human.


Why Fast Retrieval Matters

Real-estate conversations are interactive:

  • users refine budgets,
  • switch locations,
  • compare trade-offs quickly.

Algolia’s fast, low-latency retrieval makes the agent feel responsive and intelligent:

  • answers arrive instantly,
  • follow-up questions stay contextually grounded,
  • conversations flow naturally without delays.

Without fast retrieval, the experience would feel like guessing.

With Algolia, the agent feels informed, confident, and trustworthy — critical for high-stakes decisions like housing.


Thanks to Algolia Agent Studio for making it possible to focus on solving a real local problem, not the underlying search plumbing.

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