Our Tech Stack
Technologies We Work With
We pick the stack based on your product's requirements, not what we happen to know best. Here's what each technology in our toolkit is actually used for.
Laravel Development
Our primary backend framework for building secure REST APIs, admin panels, and database-driven web applications with clean, maintainable architecture.
Node.js Development
Used for real-time features, microservices, and high-concurrency backends where event-driven, non-blocking I/O gives a real performance edge.
React Development
Our default choice for interactive front-ends and dashboards, giving us a component-based architecture that scales cleanly as features grow.
Vue Development
A lighter-weight alternative to React for projects that need a fast, approachable front-end without a heavy build pipeline.
Next.js
Our go-to for SEO-sensitive web apps that need server-side rendering, App Router architecture, and strong Core Web Vitals out of the box.
Flutter
A single codebase that ships native-quality iOS and Android apps, cutting mobile development time and cost without compromising performance.
React Native
Used when a mobile app needs to share logic and components closely with an existing React web codebase for faster, consistent delivery.
Python
The backbone of our data processing, machine learning, and automation scripts — wherever heavy computation or AI logic needs to run.
Django
Our framework of choice for Python-based web backends that need built-in admin tooling, authentication, and rapid API development.
TensorFlow
Powers our custom machine learning models for prediction, classification, and computer vision tasks that need training on your own data.
LangChain
The orchestration layer behind our AI agents, chaining LLM calls, tools, and memory into reliable, multi-step automated workflows.
CrewAI
Used to build multi-agent systems where specialized AI agents collaborate, delegate, and coordinate on complex, multi-step tasks.
Pinecone
Our vector database of choice for RAG pipelines, letting AI agents search and reason over your private business knowledge in real time.
OpenAI
GPT-4o and related models power chatbots, content generation, and reasoning tasks across most of our generative AI projects.
Claude
Anthropic's Claude models handle tasks needing longer context and careful reasoning, like document analysis and complex agent instructions.
Gemini
Google's Gemini models are used for multimodal tasks — combining text, image, and data analysis in a single AI workflow.
We don't lock every project into one stack. A marketing site doesn't need the same architecture as a multi-tenant SaaS platform, and a chatbot doesn't need the same AI stack as a document-analysis agent — so the technology gets chosen after we understand the problem, not before.
