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    BackendAPIs, real-time apps, microservices

    Technology

    Node.js

    Build scalable backend services with Node.js. We use it for APIs, real-time applications, and microservices where JavaScript across the stack improves development speed.

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    5.0Google (104)    Top Rated PlusFiverrTop RatedUpworkISO 9001

    Best For

    Ideal use cases

    Teams already using JavaScript on frontend

    Applications requiring real-time features

    Projects needing fast development

    Microservices architecture

    Applications with high I/O operations

    What We Build

    Projects we deliver

    RESTful and GraphQL APIs

    Real-time chat and collaboration services

    WebSocket servers

    Microservices architectures

    Serverless functions

    Data processing pipelines

    Authentication and authorization services

    Payment processing backends

    Ecosystem

    Compatible tools & integrations

    Seamless Integrations

    Works with your existing stack

    7+ supported
    Express or Fastify for web framework
    PostgreSQL or MongoDB for database
    Redis for caching and sessions
    Socket.io for real-time features
    JWT for authentication
    Stripe or PayPal for payments
    AWS SDK or GCP SDK for cloud services

    Use Cases

    Recommended use cases

    Startup MVPs needing rapid backend development

    Real-time applications like chat or gaming

    APIs for mobile or web applications

    Microservices in larger systems

    Applications processing large amounts of I/O

    Delivery

    How we deliver

    We structure Node.js apps with modular architecture and clear separation of concerns

    Use TypeScript for type safety and better code quality

    Implement proper error handling and logging

    Set up environment variables and configuration management

    Add input validation and security best practices

    FAQ

    Frequently asked questions

    Node.js is ideal when you're already using JavaScript on the frontend, need real-time features, or want fast development. Python is better for data science, Java for enterprise systems requiring strict typing.

    Yes. We use TypeScript for Node.js projects to catch errors early, improve code maintainability, and provide better IDE support. We set up proper types for request/response and database models.

    We use connection pooling with database clients like pg (PostgreSQL) or mongoose (MongoDB). We implement proper connection management, error handling, and query optimization.

    AI

    Add AI on top of this stack

    Two common AI services that pair well with this technology, plus a fixed-scope gig to start quickly.

    Vector Database Setup

    Pinecone/Qdrant/Weaviate/pgvector setup with backups and monitoring.

    Hybrid Search & Reranking

    Improve relevance with eval-driven retrieval tuning.

    AI Hybrid Search Upgrade (Gig)

    Vector + reranker upgrade shipped as a fixed-scope pilot.

    Related

    Explore related technologies

    Frontend

    React

    Component-based UI framework

    Web applications, dashboards, SaaS platforms
    Explore
    Cloud

    AWS

    Amazon Web Services cloud platform

    Enterprise apps, scalable platforms, APIs
    Explore
    Backend

    PostgreSQL

    Relational database for production systems

    Transactional systems, analytics-backed applications
    Explore
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