Services
Engineering at Neuralix.
The technology we actually use, and the process behind how we use it — no logo wall, no fabricated partnerships.
Capabilities
Frontend
- React
- Next.js
- TypeScript
- Tailwind CSS
Backend
- Python
- Flask
- FastAPI
- Node.js
AI / ML
- scikit-learn
- PyTorch basics
- Model evaluation
- Fine-tuning workflows
Generative AI
- LLM APIs
- RAG pipelines
- Prompt engineering
- Vector databases
Cloud & Infra
- Render
- Vercel
- Docker
- GitHub Actions
Data
- PostgreSQL
- Pandas
- ETL pipelines
- Data cleaning
Process
Think deeply. Build boldly. Ship intelligently.
01
Understand
We start by understanding the actual problem — not the AI angle, the problem.
02
Research
We look at what approach fits: a simple model, a full LLM pipeline, or sometimes no AI at all.
03
Design
We design the system and the interface together, so the two never fight each other.
04
Build
We build in working increments, with something usable at every stage — not one big reveal at the end.
05
Evolve
We treat launch as a starting point. Real usage is where a product actually gets better.