Capabilities
What we work with, and what we do with it
A stack list on its own proves nothing. These are the tools we reach for, grouped by the problem they solve — and every one of them appears somewhere in the products we've shipped.
AI & machine learning
Model training, fine-tuning, and inference — from transformers to diffusion and on-device CNNs.
- PyTorch
- Hugging Face Transformers
- PEFT / LoRA
- LangGraph
- Ollama
- ONNX Runtime
- scikit-learn
- OpenCV
Retrieval & data
Vector search, hybrid retrieval, and the storage layers underneath them.
- pgvector
- Qdrant
- FAISS
- PostgreSQL
- Redis
- Kafka
Backend & APIs
Typed, documented services built to be called by something other than a demo script.
- FastAPI
- Python
- Node.js
- TypeScript
- Go
- gRPC
- WebSockets
Frontend
Accessible, fast interfaces — server-rendered by default, interactive where it matters.
- Next.js
- React
- TypeScript
- Tailwind CSS
- Framer Motion
- Flutter
Infrastructure & MLOps
Containerized services, reproducible deploys, and the observability to know they work.
- Docker
- Kubernetes
- GitHub Actions
- Terraform
- Prometheus
- Grafana
- AWS
- Vercel
Quality & evaluation
Tests for the software, evals for the models. Both run in CI.
- pytest
- Playwright
- ESLint
- RAGAS-style evals
- Load testing
How the work runs
Every engagement follows the same four steps
Discovery
We start with your problem and constraints — what success looks like, and what it will take to get there.
Plan & Estimate
A clear scope, milestones, and a realistic timeline, so you know what you're getting and when.
Build & Deploy
Iterative delivery with working software at each step — containerized and shipped, not left in a notebook.
Support & Iterate
Once it's live, we monitor, maintain, and improve it under real-world use.
Have a problem worth solving with software?
Tell us what you're building. We'll help you scope it, build it, and ship it.