AI / Jarvis Block
PromptHub Templates New

Intelligence. Built In.

Add powerful AI capabilities to your application in minutes. 10 research-backed prompt templates, text analysis, image recognition, recommendations, and content moderation—no ML expertise required.

<100ms

Inference Time

15+

AI Models

99.5%

Accuracy

100+

Languages

AI Capabilities Ready to Use

Pre-built machine learning features that would take months to build—ready to integrate in minutes.

Text Analysis

Extract insights from text with sentiment analysis, entity recognition, and key phrase extraction.

Image Recognition

Classify images, detect objects, and extract text from images with computer vision APIs.

Smart Recommendations

Personalized recommendations for products, content, or actions based on user behavior.

Content Moderation

Automatically detect and filter inappropriate content, spam, and policy violations.

Embeddings & Similarity

Generate vector embeddings for semantic search, clustering, and similarity matching.

Language Translation

Translate text between languages with high accuracy and natural fluency.

PromptHub Template Library

Prompt Engineering, Built In

10 research-backed prompt schemas ready to use. Chain of Thought, Few-Shot Learning, RAG Context, and more—each with structured sections and dynamic placeholders.

Universal

Freeform

Open-ended prompt for any task. No constraints, maximum flexibility.

Persona Agent

Role-based prompts with expertise context and behavioral guidelines.

Structured Output

Enforce JSON, tables, or specific formats in LLM responses.

Reasoning & Quality

Chain of Thought

Step-by-step reasoning for complex problem-solving tasks.

Few-Shot Learning

Teach by example with input/output pairs for consistent results.

Self-Critique

LLM reviews and improves its own output before returning.

Specialized

RAG Context

Grounded generation with retrieved documents and source citations.

Research Query

Multi-source research with structured findings and evidence.

Fact Check

Verify claims against evidence with confidence scores.

Knowledge Generation

Generate structured knowledge from unstructured data.

Dynamic Placeholders

Every template uses {{placeholder}} syntax for dynamic values. Supports strings, arrays, nested objects, and pipe transforms.

Render APIExecute APIAny LLMVersioned
prompt-render.ts
// Render a prompt template
const result = await client.prompts.render(
  "prompt_uid", {
    topic: "climate change",
    sources: ["url1", "url2"]
  }
);

AI in Three Lines

No ML pipelines. No model training. No infrastructure. Just call the API and get intelligent results.

  • Pre-trained models – Production-ready AI, no training needed
  • Simple REST API – JSON in, intelligence out
  • Scales automatically – From prototype to production
ai-example.ts
// Analyze sentiment
const sentiment = await client.ai.analyzeSentiment({
  text: "This product is absolutely amazing!"
});
// { score: 0.92, label: "positive" }

// Extract entities
const entities = await client.ai.extractEntities({
  text: "Apple CEO Tim Cook announced..."
});
// { entities: [{ text: "Apple", type: "ORG" }, ...] }

// Get recommendations
const recs = await client.ai.recommend({
  userId: "user_123",
  context: "product-page",
  limit: 5
});

AI For Every Industry

From e-commerce to customer support—add intelligence to any application.

E-Commerce

Product recommendations, review sentiment, image search, and smart categorization.

Content Platforms

Content moderation, auto-tagging, personalized feeds, and engagement prediction.

Customer Support

Ticket classification, sentiment detection, response suggestions, and priority scoring.

How It Works

From API call to intelligent response in milliseconds.

1

Send Request

Pass your text, image, or user data to the AI endpoint.

2

Process

Our optimized ML models analyze your data in real-time.

3

Get Results

Receive structured JSON with predictions and confidence scores.

4

Take Action

Use the insights to power features in your application.

Ready to Add AI to Your App?

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