< 180ms
P95 Router Latency
Loading RsFlowHub...
Perform semantic FAQ vector matching, document chunk search, and citation-backed RAG context synthesis over corporate knowledge bases.
Create and manage collections of FAQ items for semantic search matching.
/api/v1/ai/faq-collections
{
"status": "success",
"code": 200,
"data": {
"match_found": true,
"confidence": 0.94,
"matched_faq_id": "billing_04",
"question": "How can I request a refund?",
"answer": "You can request a refund within 14 days by navigating to Account Settings > Billing > Request Refund.",
"source_citation": "kb_billing_policy_v2.md"
},
"telemetry": {
"latency_ms": 142
}
}
P95 Router Latency
Language & Model Coverage
Data Persistence (Zero-Trust)
How RSFlowHub RAG, FAQ & Knowledge Base APIs delivers high-throughput inference with sub-180ms latency and guaranteed JSON contracts.
RSFlowHub RAG & Knowledge Base APIs deliver grounded information retrieval and semantic vector search over corporate documents and FAQ collections. Combining dense embeddings with strict anti-hallucination guardrails, these endpoints synthesize accurate answers with explicit citations (e.g., [Doc 1, Page 3]) in sub-200ms.
Showing 2 live endpoints with dynamic model failover, strict JSON contracts, and unified credit billing.
Create and manage collections of FAQ items for semantic search matching.
/api/v1/ai/faq-collections
Match a search query semantically against an FAQ collection using a hybrid vector-similarity algorithm.
/api/v1/ai/faq-match
Call any RAG, FAQ & Knowledge Base APIs endpoint using standard REST requests in your favorite language. Get strict JSON output with dynamic model routing and credit telemetry.
curl -X POST "https://api.rsflowhub.com/api/v1/rag/faq-match" \
-H "X-API-Key: rf_live_your_api_key" \
-H "Content-Type: application/json" \
-d '{
"query": "How do I cancel my subscription and get a refund?",
"min_confidence": 0.85
}'
import requests
url = "https://api.rsflowhub.com/api/v1/rag/faq-match"
headers = {
"X-API-Key": "rf_live_your_api_key",
"Content-Type": "application/json"
}
payload = {
"query": "How do I cancel my subscription and get a refund?",
"min_confidence": 0.85
}
response = requests.post(url, headers=headers, json=payload)
print(response.json())
const response = await fetch("https://api.rsflowhub.com/api/v1/rag/faq-match", {
method: "POST",
headers: {
"X-API-Key": "rf_live_your_api_key",
"Content-Type": "application/json"
},
body: JSON.stringify({
"query": "How do I cancel my subscription and get a refund?",
"min_confidence": 0.85
})
});
const data = await response.json();
console.log(data);
<?php
$ch = curl_init("https://api.rsflowhub.com/api/v1/rag/faq-match");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"X-API-Key: rf_live_your_api_key",
"Content-Type": "application/json"
]);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{
"query": "How do I cancel my subscription and get a refund?",
"min_confidence": 0.85
}');
$response = curl_exec($ch);
curl_close($ch);
print_r(json_decode($response, true));
{
"status": "success",
"code": 200,
"data": {
"match_found": true,
"confidence": 0.94,
"matched_faq_id": "billing_04",
"question": "How can I request a refund?",
"answer": "You can request a refund within 14 days by navigating to Account Settings > Billing > Request Refund.",
"source_citation": "kb_billing_policy_v2.md"
}
}
How RSFlowHub RAG, FAQ & Knowledge Base APIs compares to direct cloud provider SDKs and self-hosted open-source clusters.
| Platform Capability | RSFlowHub RAG, FAQ & Knowledge Base APIs | Direct Cloud SDKs | Self-Hosted Models |
|---|---|---|---|
| Anti-Hallucination | Strict Context Grounding Guardrails | Prone to Plausible Hallucinations | Requires Complex Eval Setup |
| Vector Indexing | Managed pgvector Pipeline | Requires Separate Pinecone/Weaviate | Manual Milvus/Chroma Cluster |
| Search Latency | Sub-190ms Hybrid Search | Multiple API Network Roundtrips | Depends on Dedicated Memory |
Real-world architectures deployed by engineering teams using RAG, FAQ & Knowledge Base APIs.
Match customer questions against your existing FAQ database semantically, resolving inquiries instantly without human intervention.
Search across API specs, markdown files, and code repositories to answer technical developer questions with source line references.
Allow employees to query internal employee handbooks, compliance checklists, and benefits policies securely with zero data training risk.
Technical specifications on RAG, FAQ & Knowledge Base APIs latency SLAs, concurrency limits, schema validation, and billing.
If confidence falls below your configured minimum threshold (e.g. 0.85), the API returns match_found=false alongside related fallback questions.
You can pass raw text chunks, markdown files, JSON objects, or PDF extracted text arrays.
Keyword search requires exact word matching and fails on synonyms. Vector search matches the semantic meaning and intent of the query regardless of wording.
Yes. Every generated response includes metadata indicating the exact source document ID, chunk index, and similarity confidence score.
Never. Document embeddings and context chunks are strictly isolated to your account and never used for foundation model training.
Get production API keys, access developer documentation, and test requests live in our interactive playground with 1,000 free credits.
⚡ 24h Bug Fix SLA: If you face any issues, submit them & we fix them within 24 hours.
💡 Custom APIs: Need custom AI models or APIs? Tell us and we will build them for you.