Azure Text Analytics vs TextLens API

Azure Text Analytics (now Azure AI Language) excels at named entity recognition, key phrase extraction, and opinion mining -- but has no readability scoring. TextLens API fills that gap: Flesch-Kincaid grades, SMOG, Gunning Fog, consensus grade -- without an Azure subscription, resource endpoints, or per-character pricing.

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Feature comparison

Feature Azure Text Analytics TextLens API
Readability formulas None 8 (Flesch-Kincaid, Gunning Fog, SMOG, Coleman-Liau, ARI, Dale-Chall, Linsear Write, consensus)
Sentiment analysis ✓ (positive/negative/neutral + confidence) ✓ (AFINN score + label)
Named entity recognition ✓ (people, locations, orgs, dates, quantities) ✗
Key phrase extraction ✓ ✗ (TF-IDF keywords instead)
Opinion mining ✓ (aspect-level sentiment) ✗
Language detection ✓ (120+ languages) ✗
Readability scoring None ✓ 8 formulas, consensus grade
Keyword extraction ✗ ✓ TF-IDF with relevance scores
SEO scoring ✗ ✓
Pricing model Per 1K text records (tiered) Per request (flat monthly tiers)
Free tier 5,000 text records/mo (F0 tier) 1,000 req/mo
Setup required Azure subscription, Cognitive Services resource, endpoint URL, key API key only
Authentication Ocp-Apim-Subscription-Key header + endpoint URL X-API-Key header
SDK dependency azure-ai-textanalytics (Python) HTTP only — any language

The code

Azure Text Analytics Python

from azure.ai.textanalytics import TextAnalyticsClient
from azure.core.credentials import AzureKeyCredential
client = TextAnalyticsClient(
    endpoint=AZURE_ENDPOINT,
    credential=AzureKeyCredential(AZURE_KEY)
)
result = client.analyze_sentiment([text])[0]
print(f"Sentiment: {result.sentiment}")
print(f"Confidence: {result.confidence_scores.positive:.2f}")
# No readability scoring in Azure Text Analytics.

Requires Azure subscription, a Cognitive Services resource, and a separate Python SDK. The resource endpoint URL is region-specific.

TextLens API Python

import requests
result = requests.post(
    "https://api.ckmtools.dev/v1/analyze",
    headers={"X-API-Key": TEXTLENS_KEY},
    json={"text": text}
).json()
print(result["readability"]["consensus_grade"])  # Grade 8
print(result["sentiment"]["label"])              # positive
print(result["keywords"]["top_5"])               # ["content", ...]

Readability + sentiment + keywords in one HTTP call. No Azure account. Works in Python, Go, Ruby, PHP, Node.js.

Which one to use

Use Azure Text Analytics when:

  • You need named entity recognition (people, locations, organizations)
  • You need opinion mining (aspect-level sentiment analysis)
  • You need multi-language detection across 120+ languages
  • You're already on Azure and want tight integration with other Cognitive Services

Use TextLens API when:

  • You need readability grades (Flesch-Kincaid, SMOG, Gunning Fog)
  • You want TF-IDF keyword extraction with relevance scores
  • You need SEO scoring alongside text analysis
  • You want flat pricing per request (not per text record)
  • You want to avoid Azure subscription setup for a text utility

Pricing

Azure Text Analytics charges per 1,000 text records (one record = up to 5,120 characters). S-tier pricing starts around $2/1K records for sentiment; entity recognition is priced separately. There's a free F0 tier with 5,000 text records/month with limited throughput. TextLens API: Free (1K req/mo), Starter $9/mo (25K), Pro $29/mo (100K), Team $79/mo (500K).

Azure pricing varies by region and tier — see azure.microsoft.com/pricing/details/cognitive-services/language-service/ for current rates.

Get Early Access

TextLens API is in development. Join the waitlist to get notified at launch.

From the team behind textlens — 96 npm downloads this week.

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