ServicePRIVATE KNOWLEDGE + RAG/ rag-implementation

RAG Implementation

Private knowledge base chatbots with evaluation, guardrails, and observability.

Time-to-MVP
2–6 weeks
Integrations
CRM / Ops / API
Quality
Eval + monitoring
Overview
This is for you if…
If you want a safe chatbot over internal docs.
If quality matters: eval + regression.
If you need access control + auditability.
Overview
Deliverables
Chunking + retrieval
Eval harness
Guardrails + monitoring
Overview
Outcomes
Less searching

Fast, relevant answers.

Measurable quality

Eval set + thresholds.

Stable in prod

Guardrails + monitoring + drift.

Process
Simple 3 steps
01
Discovery

Goals, data, integrations. Short audit + plan.

02
Build

Iterative delivery: prototype → production. Tests + controls.

03
Operate

Metrics, monitoring, drift. Continuous tuning.

FAQ
Short answers
Do you support private data?
+
Yes — private RAG, controlled access, auditability.
How do we measure quality?
+
Offline eval sets + production metrics and drift detection.
SEMANTIC_SPACE.exe
Live Vector Search Simulation
Security + quality
Production controls

Logging, alerts, release gates — with documented operation.

Next step
15 minutes — and scope is clear

We’ll send a short checklist, then propose timeline and first metrics.

Live viewers
16now
real-time
FREE PACK

Get the free resources

Short, high-signal updates + instant access to downloadable templates.

What you get
  • AI prompt templates (business, marketing, automation)
  • Quick audit checklist (web/AI systems)
  • Mini playbook: how to build a RAG system
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By: Dezso Mezo • UseAIEasily