AI Observability Should Address Security Requirements — Not Introduce Them
Observability that relies on foundational models requires sharing your data externally.
Fiddler utilizes in-house Fiddler Trust Models to deliver fast, accurate metrics and guardrails from within your cloud or VPC environment — no external calls necessary.
Designed from the Ground Up to Meet Enterprise Monitoring and Security Needs
Metrics-Driven LLM and MLOps in Production Environments
Protect LLMs with the Fastest Guardrails in the Industry
Proactively moderate hallucinations, toxicity, and jailbreaks using Fiddler Guardrails — delivering industry best <100ms response times* that secure LLMs with minimal impact to the user experience.
Pinpoint Issues with Intuitive Root Cause Analysis
Dive into root cause analysis on any data point without having to leave your custom charts, explore embeddings visually using Fiddler’s UMAP, and proactively identify potential risks using custom alerts.
Understand AI Activity with Highly Flexible Monitoring
Track 50+ LLM and 30 out-of-the-box ML metrics with deeply customizable charts and dashboards, featuring an intuitive UX, dual Y-axis support, and advanced segment monitoring.
One of the things that was appealing to IAS about Fiddler was its ability to customize the monitoring to specific model type, data volume and desired insights. Additionally, the dashboard views, automated alerting and ability to generate audit evidence also factored into the decision to work with Fiddler.
Kevin Alvero
Chief Compliance Officer, IAS
* Dependent on input size, geographical location, system load, or other infrastructure variability.
