High Concurrency & AI Backends

Node.js & Python Backend Engineering

Engineered for millions of requests and complex data science. Event-driven Node.js microservices, lightning-fast Python FastAPI endpoints, background task queues, and private enterprise AI models.

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Async High Concurrency

Handle tens of thousands of simultaneous client connections per node without thread-locking overhead using Node.js event loops and Python's asyncio / uvloop.

Private Enterprise AI & RAG

Python-driven Retrieval-Augmented Generation (RAG), vectorized PostgreSQL (pgvector) embeddings, and intelligent document OCR parsers that keep data on-premise.

Distributed Microservices

Decoupled service communication using RabbitMQ, Apache Kafka, or Redis Streams. Graceful degradation, circuit breakers, and containerized Docker clusters.

Server-Side Capabilities

What We Engineer With Node.js & Python

High-performance data pipelines, real-time messaging, and cognitive automation.

NestJS Enterprise Microservices

  • Strict architectural boundaries with Angular-inspired dependency injection
  • Full TypeScript types end-to-end between backend controllers and clients
  • gRPC and REST protocol transport for ultra-fast inter-service calls
  • Automated OpenAPI documentation and validation pipes

FastAPI High-Speed REST Services

  • Async Pydantic data modeling and automatic request validation
  • Performance on par with Go and Node.js using Starlette and Uvicorn
  • Direct integration with machine learning models and data science libraries
  • OAuth2 password hashing and JWT bearer token security

Celery & BullMQ Job Queues

  • Distributed background job execution with Redis and RabbitMQ
  • Task prioritization, exponential backoff retries, and dead-letter queues
  • Scheduled cron jobs for nightly database backups and report digests
  • Live queue monitoring dashboards with alert thresholds

Private LLM & RAG Pipelines

  • Vector database embedding indexing (Qdrant, Pinecone, pgvector)
  • LangChain and LlamaIndex document chunking and metadata filtering
  • On-premise LLM serving using Ollama and vLLM (Llama 3, Mistral)
  • Zero corporate data leakage — 100% private internal knowledge search

Automated Invoice & Document OCR

  • PDF invoice, purchase order, and bill of lading text extraction
  • Hybrid rule-based regex and vision AI for unstructured formats
  • Confidence scoring and human-in-the-loop exception verification
  • Automated payload insertion into Tally, SAP, or custom ERP ledgers

Telemetry & IoT Data Ingestion

  • High-throughput TCP/UDP socket servers for GPS vehicle trackers
  • TimescaleDB and InfluxDB time-series storage for sensor metrics
  • Real-time alert dispatch for geofence breaches and temperature spikes
  • Automated data rollup and compression for long-term historical storage

Frequently Asked Questions

Node.js (NestJS or Express) excels at I/O-intensive real-time tasks — live chat, WebSocket connections, IoT sensor ingestion, and lightweight microservices sharing TypeScript types with the frontend. Python (FastAPI or Django) is the gold standard for data engineering, complex numerical calculations, document OCR parsing, and private AI/LLM integration via LangChain.
We deploy Celery with Redis or RabbitMQ as the message broker, monitored via Flower. Long-running tasks like bulk PDF generation, financial reconciliations, and machine learning inference run asynchronously without blocking API responses.
Yes. Using Python, Ollama, and vLLM, we host open-source models (such as Llama 3 or Mistral) on your own private GPU servers, ensuring 100% data privacy and compliance with enterprise security policies.

Scale your backend and AI systems

Schedule an architecture session with our senior Node.js and Python engineers to discuss throughput, message queues, and AI models.

Consult With Backend Leads