Sold by: Fiddler AI
Deployed on AWS
Fiddler is the pioneer in AI Observability for responsible AI. The unified environment provides centralized controls and actionable insights to operationalize ML models, GenAI, and LLM applications with trust. Monitoring, analytics, and security capabilities address the unique challenges of building in-house and secure LLM and MLOps at scale. Fiddler helps you grow into advanced capabilities and build a framework for responsible AI practices.
Fortune 500 organizations use Fiddler across pre-production and production to deliver high performance AI, reduce costs, and be responsible in governance.
Fiddler AI (Lite Version) includes observability for 1 model, .5 GB of Data/Monthly, and our lowest level of support. No LLM functionality is included.
4.2
Overview
Fiddler AI is a unified AI observability platform for LLMOps and MLOps that enables data science and engineering teams to move beyond the experimentation and testing phases, to monitoring more high-performing models in production (including tabular, deep learning, computer vision, natural language processing, and large language models). Combine the power of Amazon SageMaker AI for training and deploying models with Fiddler AI Observability to monitor, analyze, and improve ML models to ensure high-performing, accurate, and responsible AI applications.
Fiddler AI (Lite Version) includes observability for 1 model, .5 GB of Data/Monthly, and our lowest level of support. No LLM functionality is included.
Validate: Ship more models into production and increase confidence in your models' outputs. Validate and improve models before deployment for optimal outcomes.
Monitoring: Fiddler helps you reduce costs and increase efficiencies by tracking how all your tabular, natural language processing (NLP), computer vision (CV), deep learning, and large language model (LLM) deployments are performing. Identify and mitigate model performance, drift, data integrity, hallucination, accuracy, safety, and security issues before they impact your business.
Analytics: Fiddler's model analytics tool helps you gain actionable insights from your models to make data-driven business decisions. Understand trends and outliers at the macro-level using 3D UMAP and perform root cause analysis and diagnostics to understand the micro-level issues impacting your LLM and ML applications. Pinpoint specific areas to optimize by drilling down on segments of interest.
Enterprise-level scale: Fiddler helps companies securely operationalize and scale model deployment across their ML lifecycle. Fiddler provides SOC2 Type 2 security compliance and role-based access control (RBAC) so that users across the business receive level-specific permissions to access protected environments.
Start monitoring your ML models by simply uploading your baseline dataset and register your model with Fiddler. Publish production events and start analyzing your model's performance.
With this purchase of Fiddler AI (Lite Version), you are entitled to onboard up to 1 model, .5 GB of Data/Monthly, and our lowest level of support. No LLM functionality is included. To discuss custom and Enterprise solutions, please reach out to sales@fiddler.ai .
Highlights
- Enterprise-grade AI Observability: A full stack, actionable AI Observability platform that supports predictive and generative models in production (including tabular, deep learning, computer vision, and large language models)
- Actionable Diagnostics and Insights: Quickly pinpoint and resolve issues with powerful root cause analysis and diagnostics for streamlined troubleshooting. Gain deep, actionable insights with customizable dashboards and reports, tracking model metrics tailored to your unique use case through custom metrics, empowering better business decision-making
- Intuitive User Experience: From receiving alerts to uncovering root causes and aligning model metrics with business KPIs, Fiddler delivers an intuitive experience that connects technical insights with business impact
Details
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Deployed on AWS
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Dimension | Description | Cost/12 months |
|---|---|---|
Fiddler AI | Total Contract Value | $24,000.00 |
Vendor refund policy
Please contact awsteam@fiddler.ai
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Support
Vendor support
For more documentation and support offerings, please visit our Support Center at https://docs.fiddler.ai/ or email support@fiddler.ai .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Fiddler AI
By Arize AI
Top
50
In Computer Vision
Top
25
In Observability, Software Development
Top
100
In Data Governance
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Multi-Model Type Support
Supports monitoring and observability for tabular, deep learning, computer vision, natural language processing, and large language model deployments
Performance and Drift Detection
Identifies and mitigates model performance degradation, data drift, data integrity issues, hallucination, accuracy, safety, and security issues in production deployments
Root Cause Analysis and Diagnostics
Provides powerful root cause analysis and diagnostic capabilities with 3D UMAP visualization for macro-level trend analysis and micro-level issue identification
Enterprise Security and Access Control
Implements SOC2 Type 2 security compliance and role-based access control (RBAC) for level-specific user permissions across protected environments
Customizable Analytics and Metrics
Offers customizable dashboards, reports, and custom metrics to track model performance aligned with business KPIs and enable data-driven decision-making
Agent and Application Observability
Full visibility into AI agent behavior through tree-structured traces capturing user inputs, routing logic, tool calls, memory access, and model outputs with native support for Amazon Bedrock Agents and open-source frameworks
Prompt Optimization and Testing
Prompt IDE environment enabling design, testing, and comparison of prompt versions with live inputs, outputs, and integrated evaluation results for iterative improvement
LLM and Agent Evaluation
Offline and online LLM-as-a-Judge evaluations assessing accuracy, tool-calling, planning, and goal achievement across agent workflows
Closed-Loop Improvement Workflows
Self-improving agent capabilities combining trace analysis, evaluation feedback, and golden datasets for continuous iteration and performance enhancement
Real-Time Monitoring and Alerting
Custom metrics definition and monitoring of latency, token usage, and failures with alert configuration for production issue detection and prevention
Data Quality Monitoring
Automated monitoring and alerting across data vitals with out-of-the-box anomaly detection and configurations for identifying data quality issues.
Multi-Data Type Support
Capability to monitor tabular, image, and text data types across machine learning applications and data pipelines.
Privacy-Preserving Architecture
Platform operates on processed data summaries rather than raw data, enabling privacy preservation and no-configuration deployment at scale.
Comprehensive ML Observability
Unified monitoring of model inputs, outputs, performance metrics, data drift, concept drift, and upstream data quality issues in a single platform.
Broad Integration Ecosystem
Integration with popular ML and data tools including Pandas, Apache Spark, AWS SageMaker, MLflow, Flask, Ray, RAPIDS, and Apache Kafka.
Standard contract
No
No
No
Customer reviews
Amar-Kumar
Personalized restaurant recommendations have boosted user engagement and inform data driven decisions
Reviewed on Mar 10, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case and interest in Fiddler AI is detecting and analyzing AI models. If we can analyze the AI model, it's a significant achievement for us, and we can easily implement AI features.
A specific example of how I tried to analyze and detect an AI model using Fiddler AI involves my work in the QSR domain. Imagine there is a food delivery app. Fiddler AI can be used to recommend restaurants, recipes, and nearby or favorite restaurants.
I found Fiddler AI to be the best solution in the market to analyze the QSR domain. As a QSR domain expert, we can use Fiddler AI to give personalized recommendations. If we have an application for restaurants or QSR, we can personalize the menu, homepage, and cart to a specific user. If I am an end user using an application and receiving menu choices based on my previous recommendations, that would be an eye-catching moment that we can easily achieve using Fiddler AI.
What is most valuable?
The best features that Fiddler AI offers include monitoring and managing the model, which is the best feature.
When I say monitoring and managing the model, the aspects I find most valuable are tracking performance, detecting drift, and alerting when something goes wrong. Fiddler AI helps me analyze behavior and a bunch of data, since AI is nothing but a set of data. I can track user journey and analyze user behavior.
Fiddler AI has positively impacted my organization through my exploration, even though I haven't implemented it in my company. I am an AI enthusiast, so I try to explore solutions that I can recommend to my company. Based on my exploration, I think Fiddler AI could have a positive impact if my company decided to use it. It has the potential to help my application personalize recommendations according to the user, which is the main trending feature of any QSR app available in the market.
If we can monitor the models, we are monitoring the behavior of the customer. If we can offer what the customer wants, it will directly and indirectly increase sales and automatically generate more revenue for us.
What needs improvement?
I would not say Fiddler AI needs improvements. Whatever Fiddler AI offers is great to have.
For how long have I used the solution?
I have been exploring Fiddler AI. I haven't used it particularly, but I explored it out of curiosity to learn AI. I found Fiddler AI to monitor and manage machine learning and LLM models.
What do I think about the stability of the solution?
Fiddler AI is stable from what I explored.
What do I think about the scalability of the solution?
Based on my exploration, I would rate Fiddler AI's scalability as eight on a scale of one to ten. It depends if my user base increases, which part I haven't tested, so I don't want to comment on that.
How are customer service and support?
The customer support for Fiddler AI, based on my interactions, is looking good. I'm interacting with you, and I would say I had a great experience connecting with you.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I haven't previously used an AI solution for model monitoring or AI explainability. I implemented an in-house personalization solution providing recommendations. There was a platform we used for personalization, but I can't give the name of the company due to confidentiality.
How was the initial setup?
I haven't reviewed the pricing, setup cost, and licensing while exploring Fiddler AI because it's not my area of focus. I recommended it to my organization, and they have a specific team or finance team who will review everything, and if the budget allows, they will definitely pursue it.
What was our ROI?
I definitely anticipate specific benefits and money growth if my organization adopts Fiddler AI. It will help us quickly adopt and implement solutions.
Which other solutions did I evaluate?
I did not evaluate any other AI platforms before considering Fiddler AI. In the market, there are already multiple personalized platforms. We explored Sitecore as well.
What other advice do I have?
If I get the opportunity to use Fiddler AI in my organization, I would keep it in my organization first, then go with the public and hybrid part by using the cloud. If I were to use a hybrid cloud, I would prefer to use either AWS or Azure , depending on the budget my company provides.
My advice to others looking into using Fiddler AI is simply to monitor and detect the models and user behavior. Fiddler AI is the best solution in the market, and I would give it my strongest recommendation. My overall review rating for Fiddler AI is nine out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Wahidul Nahid
Improved testing workflows have accelerated log analysis while the complex interface still needs clarity
Reviewed on Mar 09, 2026
Review provided by PeerSpot
What is our primary use case?
For work purposes, I have used Fiddler AI . During those four months, my main use case for Fiddler AI was trying to get the logs, control the results from the testing, and get the feeds from the testing. When I was doing mobile testing and web testing, I tried to manipulate the testing results. This was my use case of Fiddler AI.
What is most valuable?
There are very useful features Fiddler AI offers, but for me, the most useful ones were Traffic Inspection, Request Response Modification, Load and Performance Diagnostics, Traffic Filters, Session Organization, Security Testing Capabilities, and breaking points and debugging. Mobile and remote device testing were helpful, and I found these features very useful for me.
The most useful feature for me was response and request modification because, in most cases when doing testing on mobile, I needed to change the responses and requests through Fiddler AI. When I needed to work in a more organized way, I used filters, traffic filters, and session organization. One of the core features that helped me as well was HTTP and HTTPS traffic inspection. These have been helpful for me.
Using Fiddler AI improved my technical expertise about understanding logs, bugs, sessions, and traffic, and how to control the request and response. This knowledge is transferable, and I am still using it with other tools and in my daily life.
What needs improvement?
There can be improvements in getting error logs more clearly and in a more organized way with AI analysis of what is actually wrong and what can be the solution or how to report that error if it is a bug. That AI analysis can be helpful.
Fiddler AI is great to work with, but there can be improvements on the UI. Sometimes Fiddler AI's UI is a bit more complicated because the options sometimes feel confusing when you open the tabs and sub-tabs. This can be an improvement on the UI, and errors can be understood more clearly after an AI analysis of the logs. These are my suggestions for why I did not provide a 10.
For how long have I used the solution?
I have been using Fiddler AI for the initial four months of my junior QA engineer role.
What do I think about the stability of the solution?
I sometimes felt instability when I was using breaking point and filtering modes. I do not actually remember some of the crashes, but sometimes my PC got hanged. I do not know if it is my hardware issue or a software issue, but sometimes I felt a bit stuck doing the work.
I did not work collaboratively, but Fiddler AI is really stable, I believe.
What do I think about the scalability of the solution?
I did not work collaboratively, but Fiddler AI is really stable and I believe it is scalable.
How are customer service and support?
I did not need to reach out to the customer experience team.
Which solution did I use previously and why did I switch?
Before my current position, I was at A1QA, where I was introduced to Fiddler AI.
How was the initial setup?
Fiddler AI was deployed in my organization on my desktop. I tried to get it from the source, just installed it on my desktop, and started using it.
Initially, it was really tough for me to work with Fiddler AI because the UI was a bit more technical, and it was tough to understand. I felt the UI was a bit more congested. That is why it was tough for me initially, but when I got used to it, it was pretty easy for me.
What about the implementation team?
I did not actually need the documentation because I had a mentor in my workplace. In most cases, when I was in any problem, I would reach out to her, and she helped me a lot.
What was our ROI?
Using Fiddler AI saved me approximately one hour. If I needed three hours to complete a task initially, I could do it in two hours with Fiddler AI's help.
Which other solutions did I evaluate?
Since I started using Fiddler AI, it improved my technical expertise about the understanding of logs, bugs, sessions, and traffic, and how to control the request and response. These have been very helpful. The knowledge has been transferable, and I am still using that knowledge in other tools and my daily life. Fiddler AI really helped me to test faster. I might need to switch to any other tools that can work for only one feature. I did not need to because Fiddler AI had multiple features that I needed at the time.
What other advice do I have?
I would love to provide advice on using the request response editor and doing HTTP and HTTPS file responses about filtering the sessions. To use those features, you should use Fiddler AI. That is my recommendation. It would be great if you could finish early. The learning curve was smooth, but initially, it was an exponential curve. Initially, it was tough, but when I got used to it, it was really fast. I provided a review rating of 7 for Fiddler AI.
ibrahim d.
Best AI monitoring and Observability tool
Reviewed on Jun 11, 2024
Review provided by G2
What do you like best about the product?
There are very few good observability tools available in the market when it comes to AI model's monitoring. Fiddler's monitoring capabilities especially around LLMs are extremely powerful. Its model explaination feature is simply awesome. Integrations are very good.
What do you dislike about the product?
The tool may be quite difficult to grasp and properly used for the people very new to AI, AIOps and AI monitoring.
What problems is the product solving and how is that benefiting you?
I have been in MLOps for quite some time now. The most difficult thing always used to be post model deployment monitoring. I developed several custom monitoring but none of that could provide a centralized and complete solution. Fiddler's features are so rich and powerful, it provides a complete, centralized and data driven observability for machine learning models. I extensively use LLMs as well and for the same reason I liked the fiddler's features for LLMs.
Computer Software
Good tool for monitiong you ML data
Reviewed on Feb 09, 2022
Review provided by G2
What do you like best about the product?
Clean interface easy to find issues and data points of interest. Easy to track down issues and other minor nuances
What do you dislike about the product?
I wish there were a free version with a subset of features. Creating dashboards could be a little more intuitive but not a huge pain point.
What problems is the product solving and how is that benefiting you?
I mostly used this just for playing around with some test projects to see how it performs.