Stacks & teams
The stacks we staff
Every provider lists the same technologies. What differs here is where the engineers come from — the teams that build and run the applications in Sazinga Sarva.
AI & Machine Learning
The teams behind AI features that ship
AI/ML
Machine learning engineers who put models into production and keep them working, not notebooks that never ship.
LLM & RAG
Engineers who build retrieval-augmented systems that answer from your own data and admit when they cannot.
Data Engineering
Engineers who build the pipelines and schemas everything else depends on, and keep them trustworthy.
MLOps
Engineers who make model delivery boring — versioned, reproducible, monitored and reversible.
Frontend
Interfaces that hold up under real use
Angular
Angular engineers who have shipped and maintained large operational interfaces, not demos.
React
React engineers who have shipped operational products people use all day, not marketing pages.
Next.js
Next.js engineers who know when rendering on the server helps and when it only adds cost.
JavaScript
JavaScript and TypeScript engineers who work across browser and server rather than inside one framework.
Vue
Vue engineers who build for Vue 3 on its own terms instead of porting React habits across.
HTML/CSS
Front-end engineers who turn design into accessible, responsive markup that survives the next redesign.
Backend
APIs, data and the parts that must not fail
Node.js
Node engineers who run services in production and have been on call for the ones they wrote.
Python
Python engineers who build typed, tested services rather than scripts that grew into one.
.NET
.NET engineers who are equally at home in modern .NET and in the Framework estates still running the business.
Java
Java engineers who maintain and modernise the services larger organisations genuinely depend on.
PHP
PHP engineers who write modern PHP 8 and can also stabilise the legacy code you inherited.
Go
Go engineers who use the language where it wins — throughput, concurrency and small deployable binaries.
Mobile
Field apps that work without signal
React Native
Mobile engineers who ship apps that keep working in warehouses, on shop floors and in vans with no signal.
Flutter
Flutter engineers who get one codebase across both platforms without it feeling native to neither.
iOS
iOS engineers who build native apps that meet Apple's review bar and keep meeting it after each release.
Android
Android engineers who handle the device fragmentation that comes with any real field deployment.
PWA
Engineers who use progressive web apps where they genuinely beat shipping a native binary.
Data & BI
Turning operational data into decisions
Power BI
Power BI developers who build models that stay correct, not dashboards that need explaining every month.
Tableau
Tableau developers who design for the question being asked rather than for the gallery.
QuickSight
Analytics engineers who deliver reporting inside an AWS estate without standing up a second data platform.
D3.js
Engineers who build the visualisations a charting library cannot, and keep them readable.