AI & Machine Learning
LLM applications, RAG and predictive models
AI features fail in production when nobody measured them. We build evaluation harnesses alongside the model work, so you know accuracy, latency and cost per request before launch — and can prove the system stayed correct after every prompt or model change.
What you receive
- Production inference service with fallbacks
- Evaluation dataset and regression suite
- Vector store and ingestion pipeline
- Model governance and monitoring plan
Typical stack
- Python
- PyTorch
- LangChain
- pgvector
- Pinecone
- Claude API
- Vertex AI
What this includes
The core capabilities we bring to a ai & machine learning engagement. Scope is always tailored — this is the starting point, not a fixed menu.
RAG assistants grounded in your own documents and data
Document extraction and classification pipelines
Forecasting, recommendation and anomaly detection models
Eval suites, guardrails, PII redaction and cost controls
Have a project in mind? Let’s scope it properly.
Bring a rough idea or a full specification. Either way you leave the call with a clearer plan than you came in with — and no obligation.