Custom RAG

Custom RAG systems for any business—grounded answers from your own data

For founders, operators, and teams in any industry who need answers grounded in their own documents—not generic chatbot guesses.

Konuke designs and builds retrieval-augmented generation (RAG) tailored to your documents, tools, and permissions—so employees and customers get accurate, citeable answers instead of generic AI guesses.

How teams use custom RAG

Customer support

Instant answers from policies, product docs, and past tickets—with citations your agents can verify.

Sales & account teams

Battle cards, pricing rules, and case studies on demand without hunting through shared drives.

Operations & compliance

SOPs, contracts, and regulatory text surfaced with clear sources for audit-friendly workflows.

Internal knowledge

Onboarding playbooks, engineering runbooks, and HR policies—searchable by the people who need them.

What we build

  • Architecture and data-flow diagram for your sources and models
  • Ingestion pipeline(s) with refresh strategy and failure handling
  • Retrieval + generation stack with citation requirements
  • Access control model (tenant, team, or document-level as needed)
  • Starter eval suite and quality metrics you can run before each release
  • Handoff documentation and optional office hours during launch

Built for trust, not demos

Your knowledge, not the internet

Answers come from your approved sources—updated on a schedule you control, not from stale uploads or model hallucinations.

Retrieval you can explain

Hybrid search, reranking, and citations so users see why an answer was returned and can open the source.

Security by design

Access control, audit-friendly logging, and data boundaries chosen for your compliance story—not bolted on after launch.

Typical path to production

Phase 1 — Fit & inventory

30-minute fit call plus async source review: what to index, who may query it, and success metrics for a pilot.

Phase 2 — Pilot RAG

A narrow slice of content and users—prove answer quality, latency, and security before widening scope.

Phase 3 — Production & handoff

Hardening, monitoring, eval gates, and documentation so your team can operate and extend the system.

Pricing and packaging

Engagements typically start at $12k for a focused two-week intensive.

RAG projects vary with source count, access complexity, and deployment constraints (cloud, VPC, or on-prem). The fit call aligns on a pilot scope both sides can ship confidently.

Engagement modules

Most businesses start with discovery plus a pilot lane, then expand sources and users once quality and security are proven.

Discovery & scope

Map your knowledge sources, users, and risk profile so the RAG answers the questions your business actually asks.

  • Source inventory: docs, wikis, tickets, CRM, contracts, and APIs
  • User journeys: who asks what, and what “good” looks like
  • Data classification and access boundaries before build

Custom RAG build

End-to-end retrieval systems tuned to your content: ingestion, chunking, embeddings, retrieval, and grounded generation.

  • Pipelines for your formats (PDF, HTML, Slack, Notion, databases)
  • Hybrid search, reranking, and citation-backed answers
  • Prompting and guardrails aligned to your tone and policies

Secure rollout & ops

Ship something your team can trust: authz, logging, evals, and a path from pilot to production.

  • Role-based access so people only retrieve what they may see
  • Eval sets and regression checks when content or models change
  • Runbooks for ingestion failures, drift, and incident response

Common questions

We already tried ChatGPT on our PDFs.

Upload-and-ask breaks on updates, permissions, and traceability. A custom RAG keeps sources in sync, enforces who can see what, and returns answers with citations your team can check.

Our data is sensitive.

We design classification, residency, and vendor choices up front—private models, VPC deployment, or air-gapped options when required. No “send everything to a public API” shortcuts.

We are not a tech company.

You do not need an ML team. We deliver a working system and plain-language runbooks so your operators can own day-two ingestion and content updates.

How is this different from buying a SaaS RAG product?

Off-the-shelf tools fit generic schemas. Custom RAG fits your sources, auth model, workflows, and quality bar—including integrations your business already runs on.

Ready to scope your RAG?

Book a fit call or send your sources and constraints—we reply within one business day.

Book a fit call