Technical guides, API references, and integration resources for Tietorix AI solutions
Get up and running with Tietorix AI APIs in minutes
Sign up for a developer account and obtain your API credentials
curl -X POST https://api.tietorixai.com/auth/signup
Install our Python SDK for easy integration
pip install tietorix-ai-sdk
Initialize the client and start using AI services
from tietorix import TietorixAI
client = TietorixAI(api_key="your_key")
Complete API documentation with endpoints, parameters, and response formats
Step-by-step tutorials for integrating AI services into your applications
Software development kits and tools for multiple programming languages
Practical examples and tutorials for common AI implementation scenarios
Comprehensive API documentation for all Tietorix AI services
Secure authentication using API keys and OAuth 2.0
{
"grant_type": "client_credentials",
"client_id": "your_client_id",
"client_secret": "your_client_secret"
}Access to pre-trained models and custom AI solutions
Data transformation, cleaning, and feature engineering services
Advanced analytics and insights generation
Official SDKs and tools for seamless integration
Full-featured Python library with async support and type hints
pip install tietorix-ai
Modern JavaScript/TypeScript SDK for web and Node.js applications
npm install @tietorix/ai-sdk
Enterprise-ready Java library with Spring Boot integration
<groupId>com.tietorix</groupId>
Command-line interface for managing AI projects and deployments
curl -sSL get.tietorix.ai | sh
Real-world examples to get you started quickly
Classify images using pre-trained computer vision models
import tietorix
client = tietorix.TietorixAI(api_key="your_key")
# Classify an image
result = client.vision.classify(
image_url="https://example.com/image.jpg",
model="resnet50"
)
print(f"Prediction: {result.label}")
print(f"Confidence: {result.confidence}")
Analyze sentiment and extract insights from text data
// JavaScript example
const tietorix = require('@tietorix/ai-sdk');
const client = new tietorix.TietorixAI({
apiKey: 'your_key'
});
// Analyze sentiment
const result = await client.nlp.sentiment({
text: "I love this new AI service!",
language: "en"
});
console.log(`Sentiment: ${result.sentiment}`);
console.log(`Score: ${result.score}`);
Build and deploy predictive models with your data
import pandas as pd
from tietorix import TietorixAI
client = TietorixAI(api_key="your_key")
# Load your data
data = pd.read_csv("sales_data.csv")
# Train a model
model = client.ml.train(
data=data,
target="revenue",
algorithm="random_forest"
)
# Make predictions
predictions = model.predict(new_data)
Get help when you need it