Product
Control Plane for Agents
Systems of record for the agentic lifecycle
Explore the vision
Why Fiddler AI Observability
Test, observe, protect, and govern AI at enterprise scale
Agentic Observability
End-to-end visibility, context, and control for the agentic lifecycle
Fiddler Trust Service
Purpose-built trust models for secure, in-environment evaluation and guardrails
Guardrails
Protect agentic applications with the industry's fastest guardrails
AI Governance, Risk Management, and Compliance
Centralized control and accountability for enterprise AI governance and compliance
Responsible AI
Mitigate bias and build a responsible AI culture
ML Observability
Deliver high performing AI solutions at scale
Ready to get started?
Request demo
Solutions
Industry
Government
Mission-critical AI for defense and intelligence operations
Healthcare
Deploy agents for clinical care and patient outcomes safely
Insurance
Scale trusted agents across insurance claims, underwriting, and risk assessment
Use Cases
Customer Experience
Deliver agentic experiences that delight customers
Lifetime Value
Maximize customer lifetime value with agentic AI
Lending and Trading
Run autonomous financial AI operations at scale
Partners
Amazon SageMaker AI
Unified MLOps for scalable model lifecycle management
Google Cloud
Deploy safe and trustworthy AI applications on Vertex AI
NVIDIA NIM and NeMo Guardrails
Monitor and protect LLM applications
Databricks
Accelerate production ML with a streamlined MLOps experience
Datadog
Gain complete visibility into the performance of your AI applications
Become a partner
Case Studies
Nielsen Operationalizes Trust for a Production Multi-Agent AI Copilot
U.S. Navy decreased 97% time needed to update the ATR models
Integral Ad Science scales transparent and compliant AI products with AI Observability
See customers
Pricing
Pricing Plans
Choose the plan that’s right for you
Contact Sales
Have questions about pricing, plans, or Fiddler?
Pricing
Resources
Learn
Resource Library
Discover reports, videos, and research
Docs
Get in-depth user guides and technical documentation
Blog
Read product updates, data science research, and company news
AI Forward Summit
Watch recordings on how to operationalize production LLMs, and maximize the value of AI
Connect
Events
Find out about upcoming events
Webinars
Learn from industry experts on pressing issues facing Agentic and ML teams.
Contact Us
Get in touch with the Fiddler team
2025 Enterprise Guardrails Benchmarks Report
Which guardrails solution is right for your organization? One size never fits all — and the stakes couldn't be higher.
Read report
Company
Company
About Us
Our mission and who we are
Customers
Learn how customers use Fiddler
Careers
We're hiring!
Join fiddler to build trustworthy and responsible AI solutions
Newsroom
Explore recent news and press releases
Security
Enterprise-grade security and compliance standards
Featured News
AP News: Fiddler Raises $30M Series C to Power the Control Plane for AI Agents
WSJ Venture Capital: The $1 Trillion Hope Building Around Artificial Intelligence
CB Insights: AI Agents Need Security
Bloomberg: AI-Equipped Underwater Drones Helping US Navy Scan for Threats
We're on a mission to build trust into AI
Join us
Run free guardrails
Request demo
Generative AI and LLMOps Blogs
Read our blogs on LLMs and generative AI models and applications.
Fiddler Team
How to Prevent Rogue Agents and Accelerate Enterprise AI Deployment
Karen He, Max Bukhovko, Steve Hannah
What OMB M-26-04 Means for Federal Agencies Deploying AI
Fiddler Team
Agentic Observability: A 4-Stage Walkthrough
Fiddler Team
From Evaluations to Production: End-to-End Observability for the Agentic AI Lifecycle
Fiddler Team
Beyond Predictability: Lessons Learned from Building Agentic Systems
Amit Paka
Enterprise AI Observability in the Age of Superintelligence
Fiddler Team
The Production-Ready Agent: A Practical Playbook
Amit Paka
A Practical Guide to Monitoring and Controlling Agentic Applications
Krishna Gade, Kirti Dewan, Karen He
Anatomy of an Agent: Observing the Full Lifecycle of AI Agents
Krishna Gade, Kirti Dewan, Karen He
Agentic Observability Starts in Development: Build Reliable Agentic Systems
Cole Martin
Developing Agentic AI Workflows with Safety and Accuracy
Cole Martin
Harnessing Generative AI for Healthcare Innovation
Karen He and William Han
Introducing Fiddler Guardrails: Safeguarding LLM Applications from Safety and Security Risks
Gabriel Atkin and Karen He
Deploying Safe and Trustworthy LLM Applications at Scale with Fiddler and NVIDIA NeMo Guardrails
Cole Martin
AI Governance in the Age of Generative AI
Yuriy Pavlish and Karen He
Deploying Enterprise LLM Applications with Inference, Guardrails, and Observability
Danny Brock and Greg Stachnick
How to Monitor Your DataStax RAG Applications with Fiddler
Karen He
Scaling GenAI Applications in Production for the Enterprise
Gabriel Atkin, Karen He, and Amal Iyer
Steer and Observe LLMs with NVIDIA NeMo Guardrails and Fiddler
Karen He
LLM Monitoring: The Key to Successful LLM Deployments
Karen He
Detect Hallucinations Using LLM Metrics
Amit Paka and Krishna Gade
The New Stack for LLMOps
Karen He
AI Innovation and Ethics with AI Safety and Alignment
Danny Brock and Karen He
AI Observability: The Build vs. Buy Dilemma
Danny Brock and Karen He
Choosing Between Metrics and Inferences for Model Monitoring
Karen He
Managing the Risks of Generative AI
Anushrav Vatsa and Danny Brock
Fiddler and Domino Integration: Streamline MLOps and LLMOps to Accelerate the Production of AI Applications
Danny Brock and Greg Stachnick
Building RAG-based AI Applications with DataStax and Fiddler
Amit Paka and Danny Brock
Achieve Enterprise-Grade LLM Observability for Amazon Bedrock with Fiddler
Karen He
Monitor and Analyze LLM Hallucinations, Safety, and PII with Fiddler LLM Observability
Shohil Kothari
Building Generative AI Applications for Production
Amit Paka
How to Monitor LLMOps Performance with Drift Monitoring
Shohil Kothari
Graph Neural Networks and Generative AI
Amit Paka
Four Ways that Enterprises Deploy LLMs
Amal Iyer and Karen He
Evaluate LLMs Against Prompt Injection Attacks Using Fiddler Auditor
Shohil Kothari
AI Safety in Generative AI
Mary Reagan
Thinking of AI as a Public Service
Sree Kamireddy and Karen He
Fiddler Introduces End-to-End Workflow for Robust Generative AI
Amal Iyer and Krishnaram Kenthapadi
Introducing Fiddler Auditor: Evaluate the Robustness of LLMs and NLP Models
Mary Reagan
Best Practices for Responsible AI
Mary Reagan
LLMOps: Operationalizing Large Language Models
Mary Reagan
Top 5 Questions on Responsible AI from our Summit
Krishna Gade
An Intro to LLMs and Generative AI
Mary Reagan
Top 5 Questions on LLMOps from our Generative AI Meets Responsible AI Summit
Josh Rubin
What is ChatGPT Thinking?
Mary Reagan
Enterprise Generative AI - Promises vs Compromises
Mary Reagan
Innovating with Generative AI
Amit Paka, Krishna Gade, and Krishnaram Kenthapadi
The Missing Link in Generative AI
Mary Reagan and Krishnaram Kenthapadi
GPT-4 and the Next Frontier of Generative AI
Amit Paka and Krishna Gade
LLMOps: The Future of MLOps for Generative AI
Mary Reagan
Generative AI Meets Responsible AI Virtual Summit
