What brings you to IntenCheck?

Understand the Engine

Learn how NLP meta-programs and emotional profiling can enhance your product or workflow.

Explore basics↘

Try the Live Demo

Paste any text and instantly see the psychological analysis in our visual interactive dashboard.

Open playground↘

Build with IntenCheck

Get API documentation and start embedding deep textual insight into your CRM or app today.

View docs↘

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API for Deep Text-Based Psychological Insight

Detect NLP meta-programs, emotions, moods, and communication styles from any text and integrate the output into your product via a simple API.

What is IntenCheck?

IntenCheck is an API-first text analysis engine that detects NLP meta-programs, emotional states, and communication styles directly from natural language. It works as a language-agnostic server you can plug into any product to profile how people think, decide, and communicate in real time.

It turns raw text into rich psychological insight using NLP meta-programs, emotions, moods, and communication styles as its core dimensions. Instead of only measuring sentiment, it reveals where a person focuses attention (goals vs. problems), how they structure information (big picture vs. details), how they make choices (options vs. procedures), and how proactively they act. On top of that, it tracks dominant emotions, background mood and verbal style, giving you a multi-layered map of the author’s inner state.

How It Works

  • 1. Send Data

    Send text (or conversation logs) to the IntenCheck API.

  • 2. Multi-dimensional Analysis

    Receive structured JSON with meta-programs, emotions, mood, and communication style indicators.

  • 3. Take Action

    Use these signals to personalize content, coach users, segment audiences, or support human professionals.

Example Use Cases

  • 🤝 Coaching & Therapy Tools

    Tailor reflections and questions to a client’s meta-programs and current emotional state.

  • 🏢 HR & Talent

    Analyze interview answers and feedback for patterns in motivation and decision-making.

  • 🎧 Customer Support & CX

    Detect frustration, helplessness, or skepticism and route or respond accordingly.

  • 📚 Education & Learning

    Adapt explanations depending on whether someone prefers global over specific information, or options over procedures.

Key Features

  • NLP meta-program detection (toward/away from, internal/external reference, matching/mismatching, global/specific, options/procedures, possibility/necessity, proactive/reactive).

  • Emotion recognition (joy, calm, interest, surprise, sadness, anger, fear, guilt/shame, disgust, envy).

  • Background mood profiling (uplifted, neutral, irritable, down, worried, cynical, enthusiastic, tired).

  • Emotional communication style (warm/supportive, distant, assertive, aggressive, passive, passive-aggressive, controlling, accommodating).

  • Verbal style analysis (complaining, solution-focused, catastrophic, minimalist, analytical, critical, validating).

For Developers

API-first architecture with a simple HTTP interface, ready for scripting or low-code integration.

  • RESTful API, designed to be called from any language or platform.

  • Returns clean, structured outputs that you can plug into dashboards, rules engines, or machine learning pipelines.

  • Ideal as a building block alongside existing NLP (sentiment, topics, summarization) for deeper psychological context.

POST /api/v1/analyze

{
  "text": "I can't believe how frustrated I am with this process, but let's try to find a solution."
}

Explore IntenCheck in your browser, then connect it to your stack.

Start with the visual interface below, and move to the API when you are ready to integrate.

Input Text

Enter the text you want to analyze and base your responses on.

Metaprograms

Cognitive processing patterns

Emotional Profile ⓘ

Communication Style ⓘ

Mood State ⓘ

Tone & Posture ⓘ

Generate Target Response

Tweak the parameters above via sliders and generate a new response matching those parameters.