Knowledge Base QA (RAG)

Enterprise RAG solution: Eliminate hallucinations, improve accuracy, smart fallbacks - make your knowledge base truly useful

<5%

Hallucination Rate

>120%

NRR Lift

95%

Answer Accuracy

50ms

Retrieval Latency

Challenge

Pain points in traditional RAG systems

Hallucinations

Model drift generates false information, severely damaging user trust

Stale Knowledge

Knowledge base updates lag, unable to reflect latest information

Context Loss

Poor retrieval relevance leads to inaccurate answers

Scaling Issues

Retrieval efficiency drops dramatically as data grows

System Architecture

Solution

SkyAIApp Enterprise RAG Platform

Hybrid Retrieval Engine

Combine vector search, keyword search, and knowledge graphs for high-relevance multi-path recall

Eval-Backed Routing

Real-time confidence evaluation with automatic fallback to stronger models or human escalation

Hallucination Detection

Multi-layer validation mechanism to verify generated content consistency with knowledge base

Incremental Updates

Support real-time knowledge base updates without full index rebuild

Customer Results

<5%

Hallucination Rate

Multi-layer validation significantly reduces false information

>120%

NRR Lift

Accurate answers improve retention and conversion

95%

Answer Accuracy

Hybrid retrieval ensures high-quality answers

50ms

P95 Retrieval Latency

Optimized retrieval meets real-time requirements

Supported Vector Databases

Pinecone

Cloud-native vector DB

Weaviate

Open-source vector search

PostgreSQL

pgvector extension

Milvus

Distributed vector DB

Build Trustworthy Knowledge QA Systems

Say goodbye to hallucinations, make your knowledge base truly valuable