Tinq.ai is a developer platform that provides a suite of NLP APIs alongside an AI workspace, enabling developers and businesses to integrate text analysis, content extraction, and AI-powered workflows into their applications through a unified REST API.
NLP API Capabilities
- Sentiment Analysis: Identifies the emotional tone of text — positive, negative, or neutral — making it useful for analyzing customer reviews, support tickets, and social media content.
- Named Entity Recognition (NER): Extracts structured information such as people, organizations, locations, and brands from unstructured text.
- Plagiarism Checker: Compares submitted text against web sources to detect similarities and evaluate content originality.
- Text Generation and Rewriting: Paraphrases, summarizes, or generates content using AI language models, reducing manual writing time.
- Content Extraction: The web article extractor pulls clean text from any URL; dedicated extractors handle PDFs, Word documents, and Excel files.
- Custom Classifiers: Allows teams to build categorization models for content moderation or domain-specific tagging.
- Language Detection: Automatically identifies the language of any submitted text.
Workflows
Tinq.ai's Workflows feature allows developers to chain multiple NLP operations into a single automated pipeline, executed via one API call. For example, a workflow can extract an article from a URL, summarize it, check it for plagiarism, and classify its sentiment in sequence. This removes the need for custom orchestration code and simplifies the integration of multi-step text processing tasks.
AI Workspace
Beyond its NLP API toolkit, Tinq.ai provides an AI Workspace that connects external data sources — including Google Drive, SharePoint, Notion, Confluence, Zendesk, Jira, Salesforce, and relational databases — to AI assistants such as ChatGPT, Claude, and Gemini. The workspace indexes documents, PDFs, slides, and images using OCR, and applies permission mirroring so only authorized content is surfaced. It also supports the Model Context Protocol (MCP), enabling AI agents to treat an entire organizational knowledge base as a unified source of truth.
Use Cases
- Customer feedback analysis: Automate sentiment scoring and entity extraction from reviews, support tickets, or survey responses at scale.
- Content moderation: Use custom classifiers to flag inappropriate or off-topic content before it reaches end users.
- Editorial workflows: Chain article extraction, summarization, and plagiarism checking into a single automated pipeline for content teams.
- AI assistant grounding: Connect organizational documents and tools to AI assistants so they respond based on current, accurate internal knowledge rather than general training data.
Integration
All NLP tools are accessible through a RESTful API at https://tinq.ai/api/v2/, compatible with any programming language that supports HTTP requests. Authentication requires an API token from the Tinq.ai dashboard. The platform also integrates with Slack and Microsoft Teams for workspace connectivity.
Pricing
Tinq.ai offers a free tier for testing with no credit card required. Paid plans include Personal at $15 per month (approximately 500K tokens), Spark at $55 per month (approximately 1M tokens), and Growth at $150 per month (approximately 5M tokens). Enterprise pricing is available for high-volume API usage and full workspace integration.
