Adopt Generative AI
Safely and Effectively
Minimize business risks from using generative AI tools like ChatGPT and GitHub Copilot
Guardrails Let You Drive Fast
AI, data, and compliance leaders want to ride the generative AI wave with confidence, and not get crushed underneath it.
To govern generative AI, enterprises need a control function between business logic and business ethics to continually align large language models to serve organizational goals. This will keep businesses in control of their outputs, their brands, and their outcomes.
Keep Humans in Control of AI
Generative AI presents many novel risks, even as developers race new LLMs to market. Guardrails are essential to mitigate risk and potential damage to an organization's brand, operations, and customers.
GenAI Guardrails features an interface for tracking and explainability to stakeholders, executives, and boards who may be panicked about generative AI.
Track every GenAI use case
Use AI Registry to map all Gen AI projects, track ownership, and ensure each one meets company standards before scaling.
Apply GenAI Policy Packs
Set clear rules for using generative tools. Apply built-in policy packs to stay consistent with guidelines, regulations, and data protection.
Align GenAI use organization-wide
Test GenAI policies in a Credo AI sandbox, or deploy to your ML infrastructure, applications, and end users of generative AI apps to track GenAI usage holistically.
Is GPT generative AI?
Yes, GPT is a kind of generative technology. It can write new text, answer questions, or summarize information based on what it has learned from a lot of data.
What is the difference between generative AI and AI?
AI helps machines do things like analyze information or make choices, similar to how people think. Generative technology goes further by creating new things, like writing, pictures, or music, instead of just working with existing data.
What is an example of a generative AI?
A good example is ChatGPT, which can write text or answer questions in a human-like way.Other examples include DALL·E (creates images from text) and Google Gemini, which can understand and generate both text and visuals.
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