All Technologies Used
Motivation
The client, a property developer, needed a catalog platform to present and manage their full inventory: apartments, houses, garages, and storage units across multiple developments. Timelines were tight, requirements were well-defined, and quality was non-negotiable: the platform would be used by administrators, content managers, and end buyers. Azati applied AI coding agents throughout the development lifecycle, not to replace engineering judgment, but to compress it. Every decision, every module, and every line of production code was owned by a senior engineer from day one.
Main Challenges
The client needed a working platform, not a prototype, on a schedule that a traditional development approach couldn't meet. Using AI tools to accelerate scaffolding, boilerplate, and routine implementation freed engineers to focus time on architecture, optimization, and the business logic that actually mattered.
Real estate search is deceptively complex: users filter by property type, area, floor, price range, developer, and availability, all against a dataset that changes frequently. NLP-enhanced search needed to handle natural language queries gracefully alongside structured filters.
Content managers update listings frequently. Buyers query the catalog in parallel. Without careful caching strategy and query optimization, the system would degrade under normal usage, a common failure mode in platforms where AI-generated ORM code is never reviewed.
Our Approach
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Full Property Catalog with Admin Layer
- Multi-type property management (apartments, houses, garages, storage)
- Role-based admin and content manager interfaces
- Bulk update and status management tooling
NLP-Powered Property Search
- Natural language query parsing and mapping
- Multi-parameter structured filtering
- Relevance ranking with real-time availability
Performance Infrastructure
- Redis cache layer for high-frequency endpoints
- Celery async task queue for background operations
- Optimized ORM queries with proper indexing strategy
CI/CD Pipeline with Automated Project Tooling
- Automated test suite on every push
- Docker and Nginx production deployment
- CI/CD-triggered JIRA ticket automation
Business Value
Search quality: NLP-enhanced search adopted immediately by end users, reducing zero-result searches and increasing time-on-catalog metrics.
System performance: Query optimization and Redis caching reduced average page load times by over 60% compared to the pre-optimization baseline.
Admin efficiency: Content managers reduced listing update time by 40% through purpose-built interfaces replacing generic admin tooling.
Full code ownership: Every module documented, tested, and maintainable, the client's internal team can extend the platform without requiring Azati's continued involvement.
