ModelScan

Validate and structure LLM outputs with composable Guards

Guardrails AI is an open-source Python and JavaScript framework for validating and structuring LLM outputs using composable Guards built from a Hub of pre-built validators. It handles structured data extraction with Pydantic models, content safety checks including toxicity, PII detection, competitor mentions, and bias filtering, plus automatic re-prompting when validation fails. The Guardrails Hub offers dozens of validators from regex matching to hallucination detection via LLM judges.

Prompt registry, observability, and evaluation workflows for LLM applications.

PromptLayer is a prompt management, observability, and evaluation platform for LLM applications. Teams use its Prompt Registry, visual editor, request logs, Tables, evaluations, Tool Registry, and Skill Collections to version prompts, replay requests, compare variants, run datasets, and ship prompt changes without redeploying code. Pricing starts with Free $0 for 5 users and 2.5K requests/month, Pro $49/month, Team $500/month, and Enterprise custom.

Programmable safety rails for LLM applications

NeMo Guardrails is NVIDIA's open-source toolkit for adding programmable safety rails to LLM applications. It supports five guardrail types — input, dialog, retrieval, execution, and output rails — covering content safety, jailbreak detection, topic control, PII masking, hallucination detection, and fact-checking. The toolkit uses Colang, a domain-specific language for defining conversational constraints, and integrates with OpenAI, Azure, Anthropic, HuggingFace, and LangChain/LangGraph.