We engineer, optimize, and secure your application's data backbone—from traditional transactional databases to NoSQL stores, vector search (AI), and graph-based intelligence. Our team configures high-availability, scalable storage, backup/recovery, and delivers efficient query performance for every business and AI scenario.
Our data engineering covers schema design, migration, ETL, AI/ML data storage requirements, real-time search, and optimized queries, ensuring you get actionable insights and rock-solid storage for your web, SaaS, or enterprise apps.
Key Features
- ✔ Relational & NoSQL database modeling (PostgreSQL, MySQL, SQL Server, MongoDB, Firebase)
- ✔ Advanced indexing, normalization, partitioning, and optimization
- ✔ Cloud database solutions and managed backups
- ✔ Vector database setup (FAISS, Pinecone, Weaviate) for AI-powered search
- ✔ Graph database engineering—for smart data relationships (Neo4j)
Benefits
- 🎯 High-performant, reliable data storage for any scale
- 🎯 Support for complex analytics, AI, and high-volume business logic
- 🎯 Data integrity, recoverability, and compliance
- 🎯 Future-ready infrastructure for next-gen features (e.g., LLM-driven apps, recommendations)
Real-World Use Cases
- User/customer/lead management
- Product and content catalogs (e-commerce, SaaS, media)
- Knowledge base for AI chatbots
- Complex graph data—relationships, recommendations, social networks
- Analytics and time-series logging
