Stack
Technologies behind reliable delivery.
The stack changes by project. The standard does not: clean architecture, maintainable code, and practical delivery decisions.
A practical stack for real products.
We choose technologies that match the business goal, the product shape, and the long-term delivery reality.
01
Frontend platform
Next.js
A strong foundation for fast company websites, customer portals, product frontends, and content-rich web experiences.
02
Frontend framework
React
Component-based interface engineering for products that need reusable patterns and long-term UI maintainability.
03
Language
TypeScript
Typed application development that reduces ambiguity across frontend, backend, and API contracts.
04
Backend runtime
Node.js
Flexible backend development for APIs, workflow engines, content systems, and real-time business logic.
05
Backend and AI language
Python
A strong option for AI services, data flows, backend integrations, and systems that benefit from mature analysis libraries.
06
Database
PostgreSQL
Reliable relational data architecture for systems that need clean modeling, strong querying, and room to scale.
07
Cloud
AWS
Cloud infrastructure for secure hosting, deployment automation, and operational visibility across growing products.
08
AI platform
OpenAI
LLM-powered workflows, assistants, and AI features embedded into practical business and product use cases.
09
Containers
Docker
Containerized application packaging for consistent local, staging, and production delivery.
10
Container orchestration
Kubernetes
Orchestrated container infrastructure for teams running multi-service products at scale.
11
UI styling system
Tailwind CSS
Utility-first styling for fast interface delivery, cleaner consistency, and maintainable frontend systems.
12
Mobile framework
React Native
Cross-platform mobile development for shipping iOS and Android products with one shared engineering foundation.
13
Mobile framework
Flutter
Cross-platform app delivery with strong control over UI behavior and visual consistency across devices.
14
API layer
GraphQL
Flexible API querying for products with complex frontend data needs and multiple client surfaces.
15
Caching and messaging
Redis
In-memory caching, queues, and fast data access for products that need lower latency and stronger throughput.
16
Backend platform
Supabase
A fast product foundation for auth, database, storage, and backend workflows built around PostgreSQL.
17
Infrastructure as code
Terraform
Version-controlled infrastructure management for cloud environments that need repeatability and operational discipline.
18
Deployment platform
Vercel
Fast frontend deployment, preview workflows, and edge delivery for modern web products and company websites.
19
Database
MongoDB
Document-oriented data modeling for products with flexible schemas, high write volume, or evolving data structures.
20
Python backend framework
FastAPI
High-performance Python APIs for AI services, integrations, automation workflows, and backend product systems.
21
Python web framework
Django
Structured Python application development for products that need a mature framework and strong backend foundations.
22
Node backend framework
NestJS
Structured backend development for Node.js teams building scalable APIs, services, and internal platforms.
23
PHP web framework
Laravel
Practical backend and full-stack delivery for business systems, custom portals, and content-driven web products.
24
Commerce platform
Shopify
Commerce infrastructure for storefronts, catalog operations, and ecommerce workflows that need speed and stability.
25
CRM platform
Salesforce
CRM workflow infrastructure for sales, customer operations, reporting, and connected business processes.
26
AI platform
Claude
LLM capabilities for assistant workflows, document-heavy systems, reasoning tasks, and enterprise-facing AI features.
27
AI platform
Gemini
Multimodal AI capabilities for assistants, search, workflow automation, and product features across varied input types.
28
AI orchestration framework
LangChain
AI workflow orchestration for retrieval, tool use, multi-step reasoning, and more structured LLM application behavior.
29
Vector database
Pinecone
Vector search infrastructure for retrieval systems, semantic search, and knowledge applications built on embeddings.
30
Vector database
Weaviate
Search and retrieval infrastructure for AI systems that need semantic indexing, filtering, and knowledge-layer control.
31
Local AI runtime
Ollama
Local model runtime for teams experimenting with private AI workflows, self-hosted assistants, and controlled development environments.
32
AI ecosystem
Hugging Face
Model, dataset, and experimentation ecosystem for teams building custom AI workflows and applied ML systems.
33
LLM serving infrastructure
vLLM
Inference-serving infrastructure for teams operating high-throughput LLM workloads with more control over deployment.