Get Started with SeeMe.ai

Choose your path: Web UI for no-code simplicity or SDK for full programmatic control. From first model to production deployment in minutes.

Choose Your Path

Different approaches for different needs

🎨

No-Code Web UI

Perfect for business users, analysts, and rapid prototyping

Visual workflow builder
Drag-and-drop data upload
Pre-built templates
One-click deployment

Launch Web App

🐍

Python SDK

For data scientists, ML engineers, and automation

Full programmatic control
Jupyter notebook support
CI/CD integration
Advanced customization

See Quickstart

🔗

REST API

For backend integration and microservices

Language-agnostic
OpenAPI specification
Webhook support
Rate limiting & auth

View API Docs

Get Started in Minutes

From installation to first deployed model

01

Install SDK

# Install SeeMe.ai SDK
pip install seeme

# Or use Docker
docker pull seemeai/platform:latest

Available for Python, JavaScript, and as Docker container

02

Create & Upload Dataset

from seeme import Dataset

# Create dataset
dataset = Dataset.create(
    name="fraud-detection",
    type="structured"
)

# Upload your data
dataset.upload("./data/transactions.csv")

Supports images, text, audio, structured data, and multi-modal

03

Train Model

from seeme import Model

# Train with defaults (optimized)
model = Model.train(
    dataset=dataset,
    task="classification",
    architecture="auto"  # Or specify custom
)

# Monitor training
model.watch_progress()

Automated hyperparameter tuning, multi-framework support

04

Deploy Anywhere

# Deploy to cloud
deployment = model.deploy(
    environment="on-premise",
    region="eu-central"  # Your choice
)

# Get prediction
result = deployment.predict(data)
print(result.confidence, result.label)

Cloud, on-premise, edge, mobile—one API for all

View Full Documentation