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TextRazor

Turns unstructured text into structured data by extracting entities, topics, and sentiment, then routes those insights into your CRM or database.

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Why use Ceven?

  1. AI native TextRazor integration

    • Describe the outcome and Ceven picks the right TextRazor calls, fills the parameters, and checks the result.
    • Structured, agent friendly tool schemas so each call runs reliably instead of by guesswork.
    • Rich coverage for reading, writing, and querying your TextRazor data, across all 6 of its actions.

  2. Managed auth

    • Built in OAuth with automatic token refresh and rotation.
    • One place to manage, scope, and revoke TextRazor access.
    • Per user and per environment credentials instead of shared keys.

  3. Agent optimized design

    • Actions are tuned from real success and error rates so reliability climbs over time.
    • Full execution logs so you always know what ran in TextRazor, when, and on whose behalf.
    • The agent pauses and asks when TextRazor is unclear instead of plowing ahead.

  4. Enterprise grade security

    • Fine grained access so you control which agents and people can reach TextRazor.
    • Least privilege by default, read scopes first and only the writes a workflow needs.
    • A full audit trail of every TextRazor action to support review and sign off.

Supported tools

Every action Ceven's agents can run on TextRazor, and when to use it.

Analyze content
Use this when you need a full analysis combining multiple extractors like entities, topics, and sentiment in one call.
Classify text
Assign text to predefined categories. Use this to route support tickets or tag articles by theme.
Extract named entities
Pull people, places, and companies from text. Use this to identify who is mentioned in a document.
Extract topics
Identify the main themes and concepts in a text block to determine the general subject matter.
Correct spelling
Run deep spelling correction on input text to clean up data before it enters your database.
Extract phrases
Pull meaningful multi word expressions and key phrases that define the core message of the text.
Manage custom classifiers
Create or update your own classification categories to match your specific business taxonomy.
Manage dictionary
Create and update custom entity dictionaries to ensure the agent recognizes niche industry terms.
Analyze dependency trees
Examine the grammatical relationships between words to understand the exact structure of a sentence.
Extract entailments
Identify logical implications and phrases that can be inferred from the provided text.
Extract grammatical relations
Identify subjects, objects, and predicates to map how different entities in a sentence interact.
Extract word senses
Perform word sense disambiguation to determine the exact meaning of a word based on its context.
Get account info
Pull current account status, usage levels, and API limits to monitor consumption.
Get Account Information
This tool retrieves comprehensive information about a textrazor account, providing essential details about the account's status, usage, and limits. it returns an account object containing properties such as the current subscription plan, co
Dictionary Manager
The textrazor dictionary manager tool allows users to create, update, and manage custom entity dictionaries in textrazor. it provides endpoints for creating/updating dictionaries, listing dictionaries, getting a specific dictionary, and del
Extract Entailments from Text
This tool extracts entailments from text using textrazor's api. it identifies words or phrases that can be logically inferred from the given text by analyzing logical implications and relationships.
Extract Named Entities from Text
Extract named entities (people, places, companies, etc.) from text using textrazor's entity extraction api. the tool will identify and classify named entities within the provided text, returning detailed information about each entity includ
Extract Phrases from Text
The extractphrases action extracts meaningful phrases from input text using textrazor's phrase extraction capability. it analyzes text to identify important phrases and multi word expressions that aid in tasks like content analysis, keyword
Extract Grammatical Relations from Text
This tool extracts grammatical relations between words in the text. it identifies the relationships between different parts of sentences, including subjects, objects, and predicates. the relations extractor provides detailed syntactic analy
Spelling Correction
This tool performs spelling correction on the provided text using textrazor's deep spelling correction system. it analyzes the input text for spelling errors and provides context based corrections.
Analyze Content with TextRazor
A comprehensive content analysis tool that combines multiple textrazor extractors to perform a complete analysis of the input text. this action allows users to analyze text content with multiple extractors in a single api call.
Extract Topics from Text
A tool to extract topics from text using textrazor's topic extraction capabilities. topics represent the main themes and concepts discussed in the text, with relevance scores indicating their importance to the document.

22 actions · scroll to see them all

Frequently asked questions

Ceven monitors your TextRazor account usage in real time to prevent workflow interruptions. Depending on your TextRazor plan, you have specific limits on the number of requests per second and total characters processed per month. If a workflow hits a rate limit, the Ceven agent implements an exponential backoff strategy, pausing the execution and retrying the request automatically. You can view your current consumption by using the Get Account Information action. We recommend upgrading your TextRazor tier if you are processing thousands of large documents daily to avoid the latency introduced by these necessary retry loops during peak traffic hours.
Yes. You can use the Dictionary Manager action to create custom dictionaries. When you add your product names or industry jargon to a dictionary, TextRazor prioritizes these terms during the entity extraction process. This is critical for niche markets where a standard NLP model might mistake a product name for a common noun or a different entity type. Once the dictionary is updated, all subsequent calls to the Analyze Content action will recognize those specific terms. You can manage these lists directly through Ceven workflows without ever leaving the agent interface or logging into the TextRazor dashboard.
TextRazor provides support for several major languages beyond English. When you use the Classify Text or Analyze Content actions, you can explicitly pass a language parameter to ensure the model uses the correct linguistic rules for extraction and sentiment analysis. If you leave the language field blank, TextRazor attempts to detect the language automatically. For the highest accuracy in professional workflows, we recommend using a pre processing step in Ceven to identify the language and then passing that specific code to TextRazor to avoid misclassification of entities in multi lingual documents.
Entities are specific named objects such as Apple Inc or New York City. Topics are broader concepts or themes such as Finance or Organic Chemistry. For example, if a text mentions a new iPhone launch in Cupertino, TextRazor identifies Apple and Cupertino as entities, while labeling the topic as Consumer Electronics. Ceven allows you to use both in a single workflow. You might use entities to trigger a notification to a specific account manager and use topics to file the document into a general research folder in your cloud storage system.
The spelling correction action uses a deep learning system that looks at the surrounding context of a word rather than just comparing it to a dictionary. This means it can distinguish between two words that are spelled similarly but have different meanings based on the sentence structure. In a Ceven workflow, this is typically used as a first step. The agent cleans the raw user input first, and then passes the corrected text to the entity extractor. This significantly increases the hit rate for named entity recognition when dealing with messy data like chat logs or mobile app feedback.
TextRazor maintains strict data privacy standards. By default, the data you send via the API for analysis is not used to train their global models in a way that exposes your private information. However, it is always important to review your specific TextRazor service agreement regarding data retention. Ceven acts as a secure conduit, passing the data to the API and returning the results to your destination. We do not store the text payloads longer than necessary to complete the workflow execution, ensuring that your sensitive business intelligence remains private and secure.
Absolutely. Because Ceven is a workflow engine, it can take the structured JSON output from TextRazor and apply conditional logic. For instance, you can set a rule that says if the sentiment score is below zero point two and the entity is a Top Ten Customer, then create a high priority ticket in Zendesk. If the sentiment is positive, the agent can instead draft a thank you email. This turns a simple extraction tool into a fully automated response system that reacts to the actual meaning and tone of your incoming communication streams.
When TextRazor cannot find a match for an entity or topic, it simply returns an empty list for that specific field. Ceven handles this by using null checks in the workflow. You can configure the agent to take a specific action when no entities are found, such as flagging the document for human review or moving it to an Uncategorized folder. This ensures that no piece of data is lost and that your team knows exactly which documents required manual intervention because they fell outside the capabilities of the current NLP model or custom dictionary.

Alternatives to TextRazor

Other tools that solve a similar problem. Ceven supports these too, so you can switch or run more than one at once.

MonkeyLearn logoMonkeyLearnGoogle Cloud Natural Language logoGoogle Cloud Natural LanguageAWS Comprehend logoAWS Comprehend

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