RAG that holds up in production.
Hybrid retrieval, structured grounding, evaluation-driven tuning. We build RAG systems that stay accurate after launch — not just in the demo.
The hard part isn't retrieval. It's everything around it.
Production RAG is an engineering discipline: chunking strategy, hybrid retrieval, re-ranking, query rewriting, citation enforcement, evaluation harnesses and continuous improvement. We do all of it.
Six capabilities. One operating system.
Ingestion Pipeline
Document, web, structured-data and API ingestion with smart chunking and metadata enrichment.
Hybrid Retrieval
Dense + sparse retrieval, query rewriting, re-ranking, multi-hop reasoning.
Grounding & Citation
Strict grounding enforcement, inline citations, confidence scoring.
Evaluation Harness
Labeled QA suites, faithfulness scoring, weekly regression reports.
Freshness Management
Incremental indexing, change-data capture, content staleness alerts.
Observability
Query traces, retrieval explainability, end-to-end debugging.
From kickoff to compounding outcomes.
Scope
Use case, knowledge sources, acceptance criteria, governance.
Architect
Retrieval design, model selection, evaluation plan.
Build
Ingestion, retrieval, generation, citation, eval harness.
Tune
Iterate against eval suite until production thresholds clear.
Operate
Production monitoring, incremental indexing, continuous improvement.
Where this earns its keep.
Internal knowledge assistants
Engineering, legal, finance, ops — grounded in your real documents, with citations.
Customer-facing support copilots
KB-grounded responses with escalation, citation and quality scoring.
Compliance & policy Q&A
Regulated knowledge surfaces with strict grounding, audit trails and approval workflows.
Sales & CS enablement
Account-aware answers blending product docs, past tickets and CRM data.
Frequently asked
Pilot a RAG system.
An 8-week pilot on one knowledge domain, with measurable accuracy and grounded reporting from week one.