Engineering

Our Technology
Stack

A curated set of battle-tested technologies that power hundreds of production systems. We choose tools for their maturity, ecosystem, and performance at scale — not trends.

50+
Technologies Used
200+
Production Deployments
10B+
Daily Transactions Handled
💻

Languages

Core programming languages across our engineering practice

🟨
JavaScript / TypeScript
Frontend & Node.js backend
🐍
Python
AI/ML, data pipelines, scripting
🐹
Go (Golang)
High-performance microservices
Java / Kotlin
Enterprise backend, Android
🦀
Rust
Systems programming, WASM
🍎
Swift
Native iOS development
🔷
Dart / Flutter
Cross-platform mobile
📊
SQL
All relational databases
⚛️

Frontend Frameworks

UI frameworks and libraries for web and mobile

⚛️
React 18
Primary UI framework
Next.js 14
SSR / SSG / App Router
💚
Vue 3 / Nuxt
Selected client projects
🔷
Flutter 3
Cross-platform mobile UI
📱
React Native
JS-based mobile dev
🎨
Tailwind CSS
Utility-first styling
🧩
Radix UI / shadcn
Accessible components
🔄
TanStack Query
Server state management
⚙️

Backend & APIs

Server-side frameworks and API design tools

🟢
Node.js + Express
REST APIs, middleware
Fastify / Hono
High-perf Node.js
🐍
FastAPI
Python async REST APIs
🐘
Django + DRF
Python web framework
🔷
GraphQL (Apollo)
Graph-based APIs
📋
OpenAPI / Swagger
API spec & docs
🔌
gRPC / Protobuf
Service-to-service comms
🔗
tRPC
End-to-end type safety
🗄️

Databases & Storage

Relational, NoSQL, cache, and object storage

🐘
PostgreSQL
Primary relational DB
🐬
MySQL / Aurora
High-availability clusters
🍃
MongoDB
Document store
🔴
Redis
Cache, pub/sub, queues
❄️
Snowflake
Cloud data warehouse
🔍
Elasticsearch
Full-text search & logs
📌
Pinecone / Weaviate
Vector databases for AI
☁️
AWS S3 / GCS
Object storage
☁️

Cloud & Infrastructure

Platforms and tools for deploying at scale

🟠
AWS
Primary cloud — 80% of workloads
🔵
Google Cloud
AI/ML workloads, BigQuery
🔷
Azure
Microsoft-aligned enterprise clients
Kubernetes (EKS/GKE)
Container orchestration
🐳
Docker
Containerisation
🌿
Terraform
Infrastructure as code
Helm
Kubernetes package manager
Vercel / Cloudflare
Edge deployments
🤖

AI & Machine Learning

Models, frameworks, and MLOps tools

🔥
PyTorch
Model training & research
🧠
TensorFlow / Keras
Production inference
🦜
LangChain / LlamaIndex
LLM application framework
🤗
Hugging Face
Open-source models & datasets
🔍
OpenAI / Anthropic APIs
LLM integrations
🚀
MLflow
Experiment tracking
🏭
SageMaker / Vertex AI
Managed ML platforms
📊
Pandas / NumPy / Spark
Data processing

How We Choose Technology

🎯

Boring is Good

We prefer proven, stable technology over bleeding-edge novelty. PostgreSQL over trendy NoSQL. Kubernetes over exotic schedulers. Reliability beats cool.

🔓

Open Source First

We default to open-source tools to avoid vendor lock-in and give clients control of their destiny. Proprietary tools require compelling justification.

📏

Right-Size the Stack

A startup doesn't need Kafka. An enterprise doesn't need a monolith. We right-size the architecture to the problem, not our preferences.

Want to Know More About Our Stack?

Our engineers are happy to walk you through architecture decisions, technology choices, and how we'd approach your specific technical challenges.