Product
Fiddler AI Observability
Why Fiddler AI Observability
Overview of key capabilities and benefits
LLM Observability
AI Observability for end-to-end LLMOps
Fiddler Trust Service
LLM application scoring and monitoring with Fiddler Trust Models
ML Observability
Deliver high performing AI solutions at scale
Model Monitoring
Detect model drift, assess performance and integrity, and set alerts
NLP and CV Monitoring
Monitor and uncover anomalies in unstructured models
Explainable AI
Understand the ‘why’ and ‘how’ behind your models
Analytics
Connect predictions with context to business alignment and value
Responsible AI
Mitigate bias and build a responsible AI culture
See Fiddler in action
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Solutions
Use Cases
Government
Safeguard citizens and national security
AI Governance, Risk Management, and Compliance (GRC)
Enhance AI governance, mitigate risks, and meet compliance standards
Customer Experience
Deliver seamless customer experiences
Lifetime Value
Extend the customer lifetime value
Lending and Trading
Make fair and transparent lending decisions
Partners
Amazon SageMaker AI
Unified MLOps for scalable model lifecycle management
Google Cloud
Deploy safe and trustworthy AI applications on Vertex AI
NVIDIA NeMo Guardrails
Keep LLMs safe and accurate with Guardrails and AI Observability
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
U.S. Navy decreased 97% time needed to update the ATR models
Integral Ad Science scales transparent and compliant AI products with AI Observability
Tide drives innovation, scale, and savings with AI Observability
Conjura reduces time to detect and resolve model drift from days to hours
See customers
Pricing
Pricing Plans
Choose the plan that’s right for you
Plan Comparison
Compare platform capabilities and support across plans
Platform Pricing Methodology
Discover our simple and transparent pricing
FAQs
Pricing answers from frequently asked questions
Build vs Buy
Key considerations for buying AI Observability solution
Contact Sales
Have questions about pricing, plans, or Fiddler?
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 in MLOps and LLMOps
Contact Us
Get in touch with the Fiddler team
Support
Need help with the platform? Contact our support team
The Ultimate Guide to LLM Monitoring
Learn how enterprises should standardize and accelerate LLM application development, deployment, and management
Read guide
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
Top 10 AI Companies Shaping the Tech World
Bloomberg: AI-Equipped Underwater Drones Helping US Navy Scan for Threats
AI Observability: The Key to Unlocking the Full Potential of Large Language Models
The insideBIGDATA IMPACT 50 List for Q3 2024
We're on a mission to build trust into AI
Join us
Contact us
Request demo
Responsible AI Blogs
Learn all about responsible AI and how to build fair, transparent, trustworthy AI.
Yuriy Pavlish and Karen He
Deploying Enterprise LLM Applications with Inference, Guardrails, and Observability
Yuriy Pavlish
What the EU AI Act Really Means
Amit Paka and Karen He
The EU AI Act: A Pathway to AI Governance with Fiddler
Bashir Rastegarpanah and Karen He
Fiddler Report Generator for AI Risk and Governance
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
Legal Frontiers of AI with Patrick Hall
Shohil Kothari
AI and MLOps Roundup: April 2023
Mary Reagan and Krishnaram Kenthapadi
GPT-4 and the Next Frontier of Generative AI
Mary Reagan
Generative AI Meets Responsible AI Virtual Summit
Mary Reagan
Not all Rainbows and Sunshine: the Darker Side of ChatGPT
Amit Paka
Fiddler is Now Available for AWS GovCloud
Krishnaram Kenthapadi
How the AI Bill of Rights Impacts You
Shohil Kothari
Responsible AI by Design
Krishnaram Kenthapadi
Why You Need Explainable AI
Krishnaram Kenthapadi
With Great ML Comes Great Responsibility
Krishna Gade
AI Regulations Are Here. Are You Ready?
Shohil Kothari
Business Roundtable’s 10 Core Principles for Responsible AI
Amy Holder
XAI Summit Highlights: Responsible AI in Banking
Krishna Gade
The New 5-Step Approach to Model Governance for the Modern Enterprise
Amy Holder
A Maturity Model for AI Ethics - An XAI Summit Highlight
Krishna Gade
Where Do We Go from Here? The Case for Explainable AI
Krishna Gade
Zillow Offers: A Case for Model Risk Management
Amy Holder
Responsible AI Shifts Into High Gear
Henry Lim
The Key Role of Explainable AI in the Next Decade
Anusha Sethuraman
Responsible AI Podcast with Scott Zoldi — "It's time for AI to grow up"
Amit Paka
EU Mandates Explainability and Monitoring in Proposed GDPR of AI
Anusha Sethuraman
Responsible AI Podcast with Anjana Susarla – “The Industry Is Still in a Very Nascent Phase”
Anusha Sethuraman
Responsible AI Podcast with Anand Rao – “It’s the Right Thing to Do”
Henry Lim
Building Trust With AI in the Financial Services Industry
Henry Lim
Achieving Responsible AI in Finance With Model Performance Management
Anusha Sethuraman
Responsible AI Podcast Ep.3 – “We’re at an Interesting Inflection Point for Humanity”
Henry Lim
What Should Research and Industry Prioritize to Build the Future of Explainable AI?
Anusha Sethuraman
Responsible AI Podcast Ep.2 - “Only Responsible AI Companies Will Survive”
Anusha Sethuraman
Women Who Are Leading the Way in Responsible AI
Anusha Sethuraman
Responsible AI Podcast Ep.1 - “AI Ethics is a Team Sport”
Anusha Sethuraman
AI in Finance Panel: Accelerating AI Risk Mitigation with XAI and Continuous Monitoring
Amit Paka
Supporting Responsible AI in Financial Services
Anusha Sethuraman
How Do We Build Responsible, Ethical AI?
Anusha Sethuraman
Achieving Responsible AI in Finance
Krishna Gade
TikTok and the Risks of Black Box Algorithms
Marissa Gerchick
Identifying Bias When Sensitive Attribute Data is Unavailable
Anusha Sethuraman
Responsible AI With Model Risk Management
Amit Paka
Fed Opens Up Alternative Data - More Credit, More Algorithms, More Regulation
Krishna Gade
Explainable AI Goes Mainstream But Who Should Be Explaining?
Amit Paka
Regulations to Trust AI Are Here. And it's a Good Thing
Kent Twardock
Can Congress Help Keep AI Fair for Consumers?
