Hybrid index
Dense embeddings + BM25, fused with a learned reranker. Recall stays sane when the corpus grows.
Hybrid retrieval with citations and drift detection — answers your auditors can read.
Dense embeddings + BM25, fused with a learned reranker. Recall stays sane when the corpus grows.
Every claim cites its source span. Faithfulness + grounding evals run nightly.
Embedding distribution + retrieval-hit-rate are monitored. Alerts fire before answers degrade.
Every system we build follows this shape. Client at the edge, tools in a sandbox, traces everywhere, evaluators gating output. No black boxes, no "it works on my machine."
Three real production scenarios, replayed at observed latency. Every box is a span; every span has tokens, cost, and an eval gate. This is what shows up in your traces, not a marketing animation.
Scribe pipeline: ASR with medical lexicon, retrieve patient context + template, draft per-SOAP-section, evaluator gates clinical-safety claims.
Fixed-price, scoped to two weeks. We can share a rate sheet on request — the goal is that you leave with something concrete (architecture + spike) regardless of whether you continue with us.
Faithfulness (does the answer follow from cited docs?), grounding (are citations real?), and recall (did we find the right docs?). Every release runs the suite.
Fixed-price discovery in 2 weeks. You leave with an architecture, a working spike, and a build plan.