We choose tools that are battle-tested, well-documented, and built for production scale. Every technology in our stack earns its place through real project performance.
Component-driven interfaces with predictable state architecture and reusable UI primitives.
We use React to build modular, composable user interfaces that scale with your product. Its component model enables rapid iteration, consistent design systems, and seamless integration with modern tooling.
Use Cases
Interactive dashboards and data-rich UIs
Design system foundations
Single-page applications with complex state
Embeddable widgets and micro-frontends
Strengths
Massive ecosystem and community
Virtual DOM for efficient updates
Hooks for clean state management
Server and client rendering flexibility
Next.js
App Router workflows for high-performance rendering, SEO, and structured deployment on Vercel.
Next.js is our primary framework for production web applications. Its App Router, server components, and built-in optimizations let us deliver fast, SEO-friendly apps with minimal configuration overhead.
Use Cases
Marketing sites with dynamic content
Full-stack web applications
API routes and serverless functions
Incremental static regeneration for content-heavy sites
Strengths
Server-side and static rendering
File-based routing with layouts
Built-in image and font optimization
Edge and serverless deployment
TypeScript
Strict typing for safer refactors, clearer contracts, and long-term maintainability.
TypeScript is our default language across all JavaScript projects. It catches bugs at compile time, improves IDE support, and makes large codebases manageable over months and years of development.
Use Cases
Large-scale frontend and backend codebases
Shared type contracts between API and client
Library and SDK development
Team onboarding and code documentation
Strengths
Compile-time error detection
Rich IDE autocompletion and refactoring
Gradual adoption in existing JS projects
Strong generic and utility type system
Backend
Node.js
Event-driven API services with scalable I/O handling and modern JavaScript runtime ergonomics.
Node.js powers our backend services where JavaScript consistency across the stack matters. Its non-blocking I/O model excels at real-time features, API gateways, and high-concurrency workloads.
Use Cases
REST and GraphQL API servers
Real-time WebSocket services
Microservices and API gateways
Build tools and CLI applications
Strengths
Non-blocking event loop for high throughput
Shared language with frontend
npm ecosystem with 2M+ packages
Excellent streaming and real-time support
Python
Reliable backend services and data processing pipelines for intelligence-heavy workflows.
Python is our go-to for data pipelines, ML integrations, and backend services where its rich ecosystem of scientific and AI libraries gives us a significant productivity advantage.
Use Cases
Data processing and ETL pipelines
ML model training and serving
Automation scripts and tooling
FastAPI and Django backend services
Strengths
Best-in-class ML and data science libraries
Readable, expressive syntax
Rapid prototyping speed
Strong async support with asyncio
Cloud & Infrastructure
AWS
Cloud-native hosting, networking, and managed services optimized for scale and resilience.
We architect on AWS for teams that need enterprise-grade infrastructure. From S3 and Lambda to ECS and RDS, we design cost-effective, scalable cloud environments with proper security and observability.
Use Cases
Production hosting and auto-scaling
Serverless compute with Lambda
Managed databases and caching
CDN, DNS, and edge networking
Strengths
Broadest service catalog in cloud
Global infrastructure with 30+ regions
Mature security and compliance tools
Pay-as-you-go with reserved capacity options
Docker
Portable containers for consistent environments from local development to production.
Docker ensures what works on your machine works everywhere. We use it to package services, standardize development environments, and enable reproducible deployments across any infrastructure.
Use Cases
Containerized microservices
Local development environments
CI/CD build pipelines
Multi-service orchestration with Compose
Strengths
Environment consistency across stages
Fast, lightweight virtualization
Easy horizontal scaling
Strong ecosystem with Compose and Swarm
AI & Machine Learning
PyTorch
Flexible deep learning framework for custom model training and production experimentation.
PyTorch is our preferred framework for custom ML work. Its dynamic computation graph, intuitive API, and strong research community make it ideal for rapid experimentation and production deployment.
Use Cases
Custom model training and fine-tuning
Computer vision and NLP pipelines
Research prototyping and experimentation
Model optimization and quantization
Strengths
Dynamic computation graphs
Pythonic, intuitive API
Strong GPU acceleration support
TorchServe for production inference
TensorFlow
End-to-end machine learning tooling for training, optimization, and cross-platform inference.
TensorFlow powers our cross-platform ML deployments. From TensorFlow Lite on mobile to TensorFlow.js in the browser, it provides a complete pipeline from training to production inference anywhere.
Use Cases
Cross-platform ML deployment
On-device inference with TF Lite
Browser-based ML with TensorFlow.js
Large-scale distributed training
Strengths
Production-ready serving infrastructure
Cross-platform deployment (mobile, web, edge)
TensorBoard for training visualization
Keras API for rapid model building
Want to see our stack in action?
Every technology we use is chosen for your project's specific needs. Let's talk about what fits.