Fixed-scope RAG pipelines and agentic workflows for SMB operations
Retrieval over your docs and systems, agent workflows where they are justified, an eval harness written into the scope, and production handoff in your cloud—without an open-ended AI retainer.
Where this earns its cost
Support deflection on catalog and policy questions, exception routing for wholesale orders, and internal Q&A over SOPs and ERP exports—scoped to one workflow with measurable failure modes and one success metric.
What “fixed-scope RAG” means here
Named corpora, chunking and retrieval choices, grounded answers with citations, and pass/fail evals written before build. Scope lists what is in (SOP search, ticket assist, portal Q&A) and what is out (unbounded fine-tuning, open chatbots).
Milestones
First an eval harness and golden questions from real operators; then ingestion, chunking and citation-ready retrieval; then the admin UI, auth and staging deploy. Every milestone is a working demo, not a status report.
Eval gates before go-live
Named failure modes, groundedness and latency checks, and human fallback are acceptance criteria in the scope—so “it works in the demo” is not the bar. We propose a follow-on phase only when evals and usage justify it.
Stack and ownership
TypeScript or Python services, a vector store in your VPC or a managed option, observability, and infrastructure-as-code into your AWS or GCP account with EU data-residency notes where needed. Source, prompts, eval sets and keys stay yours.
Price
AI builds start from $14k. We quote a band after a short discovery call, then lock scope before build starts.
Ready to scope this properly?
Tell us what you are building. A senior engineer replies within one business day with scope, price, and a realistic date — before any contract.