Production-grade LLM systems.
RAG pipelines, multi-agent architectures, and LLM APIs built for reliability — with evaluation, observability, and cost control from day one.
Product teams building AI-native features that need to be trustworthy, fast, and maintainable.
Building a RAG pipeline is easy. Building one that survives production — with accurate retrieval, bounded hallucination, acceptable latency, and measurable quality — is engineering work. We've done this across healthcare CDSS, astrology interpretation, and sales intelligence products.
Full capability.
How we deliver.
Scope
Define retrieval sources, permission boundaries, and quality metrics.
Prototype
Working RAG or agent with real data and eval set within 2 weeks.
Harden
Guardrails, caching, streaming, and error handling for production load.
Measure
Continuous evaluation dashboard and feedback loop for quality improvement.
- Deployed RAG or agent system handling real queries
- Evaluation framework with regression detection
- Cost-per-query tracking and optimization
- Internal documentation for your team to extend
Need llm, rag & agent development?
Direct engagement with the founders who design and engineer the work.