Align API screenshot

What is Align API?

Align API provides safety tools for AI applications, focusing on alignment and safeguarding capabilities. The service helps developers implement guardrails and safety measures within their AI systems, making it easier to ensure models behave as intended. It's designed for teams building or deploying AI applications where safety and control are priorities. The tool operates on a freemium model, allowing users to test basic functionality before committing to paid plans. Align API targets developers, AI teams, and organisations that need to add safety layers to their AI deployments without extensive custom development.

Key Features

API-based safety checks

integrate alignment safeguards directly into your AI applications via API

Pre-built guardrails

access ready-made safety rules and alignment configurations for common use cases

Custom rule creation

define and implement your own safety parameters tailored to specific applications

Real-time monitoring

track and analyse how your AI systems behave against safety benchmarks

Integration support

connect with popular AI platforms and frameworks through documented endpoints

Pros & Cons

Advantages

  • Straightforward API integration means minimal disruption to existing workflows
  • Freemium model lets you experiment with safety features before purchasing
  • Focused specifically on AI safety rather than being a general-purpose tool
  • Reduces the need to build safety systems from scratch

Limitations

  • Effectiveness depends on how well you define and configure your safety rules
  • Limited public documentation on advanced customisation options
  • Pricing and feature details for paid tiers are not clearly published

Use Cases

Adding safety checks to chatbot applications before they interact with users

Implementing content filters in generative AI systems

Ensuring AI models stay within defined ethical boundaries in production

Testing AI applications against known safety risks during development

Monitoring deployed models for unexpected or unsafe behaviour patterns