Launching Verdic Guard — Keep LLM outputs aligned and hallucination-free

Prompt engineering works in demos—but breaks in production. As LLM workflows get longer and more complex, outputs drift, hallucinate, or violate intent in ways prompts and retries can’t reliably prevent.

Verdic Guard (https://www.verdic.dev/ )adds a runtime validation and enforcement layer between the LLM and your application. Every output is checked before it reaches users—against defined scope, contracts, and constraints—so behavior stays predictable and auditable.

It’s not a model or a prompt library. It’s trust infrastructure for LLMs: built to prevent hallucinations, enforce intent, and make AI outputs defensible in real systems.

We’re launching today and would love feedback from teams running LLMs in production:

• How do you handle hallucinations today?

• Where do prompts or monitoring fall short for you?

• What would you want from a runtime enforcement layer?