As organizations multiply their Generative AI use cases, leaders are trying to get a handle on the question, “How much will it all cost?”
With Cost Guard, IT teams can analyze up-to-the-minute data on costs and LLM usage across all teams. Prebuilt dashboards provide detailed reports by use case, user, or project, and a fully auditable log of LLM usage allows for precise cost tracking and internal re-billing.
DIVE DEEPER INTO COST GUARD
Ritu Jyoti
Group VP, AI and Automation Research at IDC (source)
Built-in usage controls help you maintain data security, ensure reputational integrity, and avoid unintended harm from AI apps.
Safe Guard evaluates requests and responses for sensitive information or malicious acts, whether that’s personally identifiable information (PII), toxic content, forbidden terms, or attempts at prompt injection. It can then take appropriate action, such as redacting sensitive information before sending the request to the LLM, blocking the request entirely, and/or alerting an admin.
LEARN MORE ABOUT PROTECTING SENSITIVE DATAEnsure high quality from proof of concept (POC) to production with standardized tooling and automated LLMOps for LLM evaluation and monitoring.
Dataiku Quality Guard provides GenAI-specific quality metrics and side-by-side comparisons of model results to ensure you deploy the highest performing AI system.
Cost monitoring is important, but reducing costs wherever possible is also crucial.
The Dataiku LLM Mesh provides the option to cache responses to common queries. That means no need to regenerate responses, offering both cost savings and a performance boost. If self-hosting, you also have the power to cache local Hugging Face models to reduce the cost to your storage infrastructure.
Cost savings are automatically visualized in Cost Guard dashboards, so you can refine and reinforce your caching strategies.
EXPLORE THE DATAIKU LLM MESH
