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
Blog
/
Data Science
Data Science Blogs
Dive into key concepts, terminology, and cutting-edge research in data science.
August 10, 2023
/
Bashir Rastegarpanah and Karen He
Fiddler Report Generator for AI Risk and Governance
Data Science
Responsible AI
Product
July 10, 2023
/
Amal Iyer and Karen He
Evaluate LLMs Against Prompt Injection Attacks Using Fiddler Auditor
Generative AI and LLMOps
Data Science
May 30, 2023
/
Murtuza Shergadwala
Making Image Explanations Human-Centric: Decisions Beyond Heatmaps
Data Science
April 20, 2023
/
Josh Rubin
What is ChatGPT Thinking?
Data Science
Generative AI and LLMOps
February 9, 2023
/
Murtuza Shergadwala
Human-Centric Design For Fairness And Explainable AI
Bias and Fairness in AI
Data Science
Explainable AI
February 6, 2023
/
Bashir Rastegarpanah
Monitoring Natural Language Processing and Computer Vision Models, Part 3
Model Monitoring
Data Science
February 1, 2023
/
Ankur Taly
Expect the Unexpected: Why Model Robustness Matters
MLOps
Data Science
December 15, 2022
/
Amal Iyer
Monitoring Natural Language Processing and Computer Vision Models, Part 2
Model Monitoring
Data Science
October 3, 2022
/
Bashir Rastegarpanah
Monitoring Natural Language Processing and Computer Vision Models, Part 1
Model Monitoring
Data Science
August 1, 2022
/
Murtuza Shergadwala
Detecting Intersectional Unfairness in AI: Part 2
Bias and Fairness in AI
Data Science
May 16, 2022
/
Murtuza Shergadwala
Measuring Data Drift with the Population Stability Index (PSI)
Data Science
April 4, 2022
/
Murtuza Shergadwala
Detecting Intersectional Unfairness in AI: Part 1
Bias and Fairness in AI
Data Science
May 13, 2021
/
Avijit Ghosh
Measuring Intersectional Fairness
Data Science
Bias and Fairness in AI
February 5, 2021
/
Malhar Jere
A Practical Guide to Adversarial Robustness
Data Science
May 14, 2020
/
Marissa Gerchick
Identifying Bias When Sensitive Attribute Data is Unavailable: Geolocation in Mortgage Data
Bias and Fairness in AI
Data Science
May 1, 2020
/
Marissa Gerchick
Identifying Bias When Sensitive Attribute Data is Unavailable: Exploring Data From the Hmda
Bias and Fairness in AI
Data Science
April 24, 2020
/
Ankur Taly
[Video] AI Explained: What are Integrated Gradients?
Explainable AI
Data Science
March 20, 2020
/
Ankur Taly
AI Explained Video Series: What are Shapley Values?
Explainable AI
Data Science
March 5, 2020
/
Ankur Taly and Aalok Shanbhag
Understanding Counterfactual and Attribution Explanations in AI
Data Science
Explainable AI
March 4, 2020
/
Marissa Gerchick
Identifying Bias When Sensitive Attribute Data is Unavailable: Techniques for Inferring Protected Characteristics
Bias and Fairness in AI
Data Science
February 27, 2020
/
Marissa Gerchick
Identifying Bias When Sensitive Attribute Data is Unavailable
Bias and Fairness in AI
Responsible AI
Data Science
August 13, 2019
/
Dan Frankowski
Integrated Gradients vs SHAP: How Should You Explain Your Predictions?
Data Science
July 31, 2019
/
Dan Frankowski and Ankur Taly
Causality in Model Explanations and in the Real World
Data Science
July 22, 2019
/
Dan Frankowski
Debugging Predictions Using Explainable AI
Data Science
June 3, 2019
/
Dan Frankowski
A Gentle Introduction to GA2Ms - A White Box Model
Data Science
May 8, 2019
/
Dan Frankowski
Humans Choose - AI Does Not
Data Science
April 23, 2019
/
Dan Frankowski
A Gentle Introduction to Algorithmic Fairness
Bias and Fairness in AI
Data Science