Text Analytics Software-As-A-Service

Extract Actionable Data from Text for Customer Relationship Management

Customer Experience Analytics | Voice of the Customer | Brand Perception| Market Research

Aspect-Based Sentiment Analysis | Keyphrase extraction | Topic categorization | Intention Detection

See demo

Fine-Grained Analysis

Detect keyphrases, topical categories, sentiment and intention in each sentence of a document.

High accuracy

Significant accuracy gains on generic NLP tools due to customization to industries and use cases.

Easy Integration

Integrate NLP into your software in several lines of code or use it directly from Microsoft Excel.

High availability

Uptime over 99.9% based on the past six months, near-linear scalability for large volumes of data.

Prebuilt Customizations

To maximize accuracy, use prebuilt customizations for domains like Retail or Electronics, out-of-the-box.

Self-service access

Create or upload your own categorization and sentiment lexicons, overriding default functionalities.

Customer Feedback

Analyze free-text customer comments in product reviews, web surveys, help desk and CRM records.

Social Media

Analyze topics and sentiment around brand mentions on social media and discussion forums.

Try it


Monthly price

  • API calls** per day
  • Per each extra call
  • Keyphrase extraction
  • Topic categorization
  • Sentiment analysis
  • Intention analysis
  • Domain customization



  • 100
  • $0.05



  • 1,000
  • $0.02



  • 3,000
  • $0.01



  • 10,000
  • $0.005



  • Unlimited
  • $0

* Academic research projects are given free-of-charge access, please get in touch.

** One API call can include text of max. 10,000 characters.

Get Started

Step 1. Choose analysis types

Decide on what types of analysis you will need, choosing any combination of: keyphrase extraction, topical categorization, sentiment analysis, intention analysis.

Step 2. Select a pricing plan and subscribe

Create an account on Mashape or 3Scale, the API management platforms, and subscribe to the GetSentiment API. mashape tutorial 3scale tutorial

Step 3. Optional Customization

Decide on how to customize the system to your project, choosing between:

  • A prebuilt domain: Retail, Hospitality, Electronics, Automotive, or Telecommunications. tutorial
  • Creating your own domain, by uploading external sentiment lexicons that will extend either the general-language system or any of the prebuilt domains. tutorial

Step 4. Integrate API into your work flow

Use the API in your software or directly from Microsoft Excel:

Code Examples

Client Request

                                import urllib, urllib2, json
from pprint import pprint


text = "The food was great, but the service was slow."
headers = {'X-Authorization': YOUR_ACCESS_KEY}
params = {'text': text, 'categories': 1, 'sentiment': 1,
            'annotate': 1}

request = urllib2.Request(URL, urllib.urlencode(params),
opener = urllib2.build_opener(urllib2.HTTPHandler)
response = opener.open(request)

data = json.loads(response.read())

                                require 'rubygems'
require 'rest_client'

values = {
     "text" => 'The food was great, but the service was slow.',
     "categories" => 1,
     "sentiment" => 1,
     "annotate"=> 0

headers  = {
     "content_type" => "application/json; charset=utf_8",
     "X-Authorization" => YOUR_ACCESS_KEY

response = RestClient.post url, values, headers

puts response
$ch = curl_init();
$headers = array("Content-Type: application/x-www-form-urlencoded; charset=UTF-8", "X-Authorization: YOUR-ACCESS-KEY");
curl_setopt($ch, CURLOPT_URL, YOUR_ACCESS_URL);
curl_setopt($ch, CURLOPT_HEADER, FALSE);
curl_setopt($ch, CURLOPT_POST, TRUE);
$fields = array('text'=>"The food was great, but the service was slow.", 'lang'=>'en', 'keywords' =>1, 'sentiment'=>1, 'annotate'=>1);
$postvars = '';
foreach($fields as $key=>$value) {
    $postvars .= $key . "=" . $value . "&";
curl_setopt($ch, CURLOPT_POSTFIELDS, $postvars);
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$response = curl_exec($ch);
echo $response;

params <- list(
    text="The food was great, but the service was slow.",
headers <- add_headers("X-Authorization"="YOUR_ACCESS_KEY")

response <- POST(


content(response, "parsed", "application/json")

Server Response

    "doc_id": "0",
    "sentiment": {
        "neg": 50.0,
        "pos": 50.0
    "categories": {
        "service": {
            "sentiment": {
                "neg": 100.0,
        "food": {
            "sentiment": {
                "pos": 100.0

Get MS Excel Add-on


Creation of custom classifiers

To maximize accuracy and insight, we develop custom classifiers that match specifics of your domain, project, and use cases.

Data collection

We assist with collection of relevant data for your project from social media, discussion boards, and the general web, including collection of historical data.

Data processing

For greater efficiency, we perform offline bulk processing of already collected datasets.

Data analysis

We carry out with statistical analysis of the data, both in textual and structured formats, data visualization and exploration.

Integrated solutions for web, email, and SMS

We develop integrated solutions for customer feedback collection via web surveys, email and SMS questionnaires, alerting service, data analysis and visualization.

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