Nelfet.
capability · 01
Applied AI & GenAI
Nelfet builds AI and GenAI systems that reach production — agents with defined tool boundaries, RAG pipelines grounded in your data, and copilots wired into real workflows.
capabilities
What we build
01Autonomous agents with tool scopes, fallback paths, and human checkpoints
02RAG pipelines over proprietary data with source attribution and hallucination controls
03Copilots embedded into existing products via API, widget, or SDK
04Structured extraction, classification, and summarization at production throughput
05Evaluation harnesses: test sets, automated scoring, and prompt versioning
outcomes
What you are left with
01A production system with defined SLOs — not an inherited notebook
02Evaluation tied to business cases, not benchmark scores
03Full observability across every model call, token, and retrieval step
04Prompt and retrieval decisions versioned so knowledge stays in the system
approach
We start from the decision the AI supports and work backward to data, retrieval, and prompts. Week one includes a representative evaluation set from real cases — the permanent quality gate. Safety, cost, and latency are first-class constraints from sprint one, not pre-launch concerns.
more capabilities
Explore the rest of the practice
02
Product Engineering
Nelfet builds web, mobile, and backend systems where quality is a structural property: typed interfaces, clear module boundaries, and test coverage that makes deploys predictable.
03Data & ML Engineering
The quality ceiling of any intelligent product is set by the data and engineering under it. Nelfet builds ingestion pipelines, feature stores, and evaluation frameworks as production-grade engineering.
04Platform & Cloud
Nelfet builds cloud platforms designed for AI's full operational surface — infrastructure as code, least-privilege access, and observability deep enough to answer what failed and at what cost.
05Product Design
Nelfet designs interfaces that make intelligent software legible — surfacing capability clearly, communicating uncertainty honestly, and giving users an accurate mental model of what the system can do.