Veloptin Documentation

Welcome to the Veloptin Enterprise AI platform documentation. Learn how to operationalize AI across your enterprise with confidence, governance, and scale.

Note: You are viewing the latest version of the documentation (v2.0).

What is Veloptin?

Veloptin is a comprehensive Enterprise AI platform designed to help organizations connect data, manage models, govern responsibly, and deploy AI applications to production. It bridges the gap between experimental AI and reliable, scalable business operations.

Key Capabilities

  • Agent Orchestration: Build complex workflows with autonomous agents.
  • Governance & Compliance: Enforce policies and guardrails automatically.
  • Unified Catalog: Centralize management of models, datasets, and prompts.
  • Secure Execution: Run AI workloads in isolated, private environments.

Quick Start Guide

Get up and running with Veloptin in minutes. Follow these steps to deploy your first AI agent workflow.

1. Install the SDK

Veloptin provides a Python SDK for easy integration with your existing data science workflows.

pip install veloptin-sdk

2. Initialize the Client

Authenticate with your API key to start interacting with the platform.

import veloptin client = veloptin.Client(api_key="your_api_key_here")

3. Create a Simple Workflow

Define a basic agent that summarizes text.

workflow = client.workflows.create( name="Text Summarizer", agent="gpt-4-turbo", prompt="Summarize the following text in 3 bullet points." ) result = workflow.run(input_text="Veloptin is an enterprise AI platform...") print(result)

Agent Workflows

Agent Workflows are the core of the Veloptin platform. They allow you to chain together multiple AI agents, data retrieval steps, and human approval gates into a single, executable process.

Workflows can be designed visually in the Studio or defined programmatically via the SDK.

Policy Management

Ensure your AI applications adhere to corporate standards and regulatory requirements using our Policy Engine.

  • PII Redaction: Automatically detect and mask sensitive information.
  • Topic Guardrails: Prevent models from discussing off-limits topics.
  • Audit Logging: Keep a complete record of all AI interactions.