Retrieval and agentic systems that survive month nine, not just the demo. We start with an eval harness against your real corpus, then build the pipeline that moves the number that matters.
What we do
Eval harness first
Before architecture, we build the harness that tells us whether a change helped. No vibes — measured retrieval and answer quality on your data.
Hybrid retrieval
Lexical + vector retrieval tuned per domain, with chunking and metadata strategies that match how your documents actually read.
Governed reasoning
Frontier models behind governed prompts, citation-first answers, and provenance preserved end-to-end for audit.
Agentic workflows
LangGraph-style orchestration with bounded tools, retries, and human checkpoints where the stakes demand them.
What you walk away with
- Domain eval suite + baseline scores
- Production retrieval pipeline
- Prompt and tool governance layer
- Cost and latency model
- Observability + regression dashboard