Feature & Topic Sentiment Breakdown
Categorizes review text into specific features (e.g. pricing, UI, customer support, build quality) with sentiment scores.
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Sub-200ms customer review intelligence API for sentiment score, feature feedback, emotion tagging, and churn risk scoring.
https://www.rsflowhub.com/api/v1/ai/review-analyze
Product & App Store Review Sentiment Analysis API is a production-ready cloud REST API endpoint hosted on RSFlowHub designed for developers building high-throughput web, mobile, and AI agent applications. It accepts structured JSON payloads via POST /api/v1/ai/review-analyze, executes sub-180ms inference across global edge regions, and returns deterministic, type-safe JSON envelopes without unpredictable hallucination.
X-API-Key Header
curl -X POST "https://www.rsflowhub.com/api/v1/ai/review-analyze" \
-H "Content-Type: application/json" \
-H "X-API-Key: rsh_live_your_api_key_here" \
-d '{"review":"The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.","rating":4,"context":"Italian restaurant in downtown New York"}'
<?php
$client = new \GuzzleHttp\Client();
$response = $client->post('https://www.rsflowhub.com/api/v1/ai/review-analyze', [
'headers' => [
'Content-Type' => 'application/json',
'X-API-Key' => 'rsh_live_your_api_key_here',
],
'json' => array (
'review' => 'The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.',
'rating' => 4,
'context' => 'Italian restaurant in downtown New York',
),
]);
echo $response->getBody();
const response = await fetch('https://www.rsflowhub.com/api/v1/ai/review-analyze', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-Key': 'rsh_live_your_api_key_here'
},
body: JSON.stringify({"review":"The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.","rating":4,"context":"Italian restaurant in downtown New York"})
});
const data = await response.json();
console.log(data);
import requests
url = "https://www.rsflowhub.com/api/v1/ai/review-analyze"
headers = {
"Content-Type": "application/json",
"X-API-Key": "rsh_live_your_api_key_here"
}
payload = {"review":"The food was absolutely delicious and the service was amazing! However, it was a bit overpriced.","rating":4,"context":"Italian restaurant in downtown New York"}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
Categorizes review text into specific features (e.g. pricing, UI, customer support, build quality) with sentiment scores.
Flags reviews where positive text contradicts 1-star ratings or negative text accompanies 5-star ratings.
Measures customer emotional intensity, disappointment levels, and churn risk probability.
Tailored for Amazon, Google Maps, Apple App Store, Google Play Store, G2, and Trustpilot reviews.
See how developers integrate this API endpoint into production apps.
Analyze daily mobile app store reviews to automatically flag software bugs, login crashes, and feature requests.
Detect recurring product defect complaints across thousands of Amazon and Shopify buyer reviews.
Extract cleanliness, staff behavior, and location sentiment scores from Google Business reviews.
Comparing RSFlowHub's specialized API gateway vs raw multi-turn LLM prompts vs legacy regex rules.
| Evaluation Metric | RSFlowHub API | Raw LLM Prompts | Legacy Regex / Rules |
|---|---|---|---|
| Response Structure | Strict typed JSON envelope | Unstructured markdown or chat format | Brittle custom regex tuples |
| Latency Performance | 120ms - 220ms edge cached | 1,500ms - 4,000ms streaming | 50ms (Zero semantic capability) |
| Pricing Model | Flat 3 credit/request | Volatile token-based billing | High server maintenance overhead |
| Multi-Turn Hallucination | Zero (Deterministic validators) | Frequent schema drift & hallucinations | No semantic AI intelligence |
| Developer Integration | 3 lines cURL, PHP, JS, Python | Complex prompt engineering & retry loop | Fragile manual rule maintenance |
review
string
Raw review text payload to analyze.
rating
integer
Star rating value (1 to 5).
language
string
Review language code (e.g. "en", "es", "fr").
context
string
Product category or business domain context (e.g. "Italian restaurant in NYC").
All API endpoints return uniform JSON envelopes with status code, execution metadata, and data payload.
{
"status": "success",
"code": 200,
"message": "Processed successfully",
"data": {
"result": "Sample output result"
},
"meta": {
"credits_deducted": 3,
"execution_time_ms": 142
}
}
Everything you need to know about integrating and using Product & App Store Review Sentiment Analysis API.
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