Deterministic guardrails for AI systems. Prevent hallucinations, enforce execution contracts, and ensure predictable LLM outputs.
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Maker
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Most agentic AI systems still rely on prompt engineering and hardcoded rules. That works in demos—but breaks in production, where LLMs drift, hallucinate, or violate intent across long workflows.
Verdic Guard adds a validation and enforcement layer between your AI and your application. It keeps outputs aligned with project intent, enforces contracts, and produces predictable, auditable responses your users can trust.
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Maker
Hi everyone — founder here 👋
Verdic came out of frustration with AI systems that work well in demos but behave unpredictably once embedded into long, real-world workflows.
I’d especially love feedback from folks running LLMs or agentic systems in production — where do you see output reliability breaking down most often?
Replies
Hi everyone — founder here 👋
Verdic came out of frustration with AI systems that work well in demos but behave unpredictably once embedded into long, real-world workflows.
I’d especially love feedback from folks running LLMs or agentic systems in production — where do you see output reliability breaking down most often?