Sold by: Patronus AI
The Patronus AI Platform is the leading automated AI evaluation and security product. The Platform enables enterprise development teams to score LLM performance, generate adversarial test cases, benchmark LLMs, and more. Customers use Patronus AI to detect LLM mistakes at scale and deploy AI products confidently.
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Overview
The Patronus AI Platform enables engineering teams to test, score, and benchmark LLM performance on real world scenarios, generate adversarial test cases at scale, monitor hallucinations and other unexpected and unsafe behavior, and more.
Customers use the Patronus AI Platform as soon as they have any kind of an LLM or LLM system in their hand. The platform is primarily used in 2 key parts of the user journey: AI product pre-deployment and AI product post-deployment. The product is typically used with not just LLMs, but also retrieval-based LLM systems, agents, routing architectures, and more. There are also 2 types of key product offerings: 1) cloud-hosted solution, and 2) on-prem self-hosted offering.
For pre-deployment: Customers use several features in the web platform for offline LLM evaluation and experimentation, all in one place. In the Evaluation Run workflow, customers can select or define parameters like the LLM and its associated settings, evaluation dataset, and criteria.
For post-deployment: Customers use the Patronus API and the LLM Failure Monitoring dashboard for LLM testing and evaluation in CI and production. The API solution allows customers to validate, log, and address LLM failures in real-time. To accompany the API and manage the alerts, there is also an LLM Failure Monitoring dashboard in the web platform to visualize, filter, and aggregate statistics on LLM failures.
Highlights
- Retrieval-Augmented Generation (RAG) Testing: Verify that your LLM-based retrieval systems consistently deliver reliable information using our retrieval evaluation API.
- Evaluation Runs: Leverage our managed service for evaluations to auto-generate test suites, score model performance on real world scenarios, benchmark LLMs, and more.
- LLM Failure Monitoring: Continuously evaluate, track, and visualize LLM system performance for your AI product in production.
Details
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Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Evaluation Samples | Total number of samples evaluated using Patronus AI Platform. | $1,000,000.00 |
Vendor refund policy
If you cancel your subscription within 48 hours of purchase, you can get a full refund. All other refunds would happen on a case-by-case basis. Reach out to contact@patronus.ai to request a refund.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
We have a 24-hour response time SLA for all buyers. Please reach out to contact@patronus.ai if you are experiencing any issues.
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.
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By Patronus AI
By Vellum
By NeuralSeek
Top
100
In Testing
Top
25
In AIOps
Top
10
In Edit/Processing-Text, Natural Language Processing, Generative AI
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
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Customer service
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AI generated from product descriptions
Retrieval-Augmented Generation Testing
Verification of LLM-based retrieval systems through retrieval evaluation API to ensure consistent delivery of reliable information.
Automated Test Suite Generation
Auto-generation of test suites and scoring of model performance on real-world scenarios with benchmark capabilities for LLMs.
LLM Failure Monitoring and Visualization
Continuous evaluation, tracking, and visualization of LLM system performance in production environments with failure aggregation and filtering capabilities.
Adversarial Test Case Generation
Generation of adversarial test cases at scale to detect hallucinations and unexpected unsafe behavior in LLM systems.
Real-time LLM Validation and Logging
Real-time validation, logging, and addressing of LLM failures through API integration with support for CI and production environments.
Prompt Engineering and Comparison
Side-by-side comparisons between multiple prompts, parameters, models, and model providers across test cases for optimization.
Workflow Orchestration
Ability to prototype and deploy AI workflows that chain business logic, data, APIs, and dynamic prompts for various use cases.
Evaluation and Testing Framework
Creation of test case banks to evaluate and identify optimal prompt and model combinations across multiple scenarios.
Semantic Search and Retrieval
Document retrieval capability to extract company-specific data and use it as context in LLM calls.
Monitoring and Proxy Infrastructure
Reliable proxy layer connecting applications to model providers with request tracking for debugging and quality monitoring.
Multi-Agent Orchestration
Build and manage multiple agentic generative AI solutions from a single platform with ability to assign Large Language Models to agents and switch between LLMs for optimization and cost savings
Retrieval Augmented Generation with Governance
Point and click governance and guardrails for Retrieval Augmented Generation outputs with Provenance, Coverage and Confidence Scores, and Semantic Analytics visibility
Hallucination and PII Mitigation
Enterprise observability and control mechanisms to mitigate risks of Large Language Model hallucination, misinformation, and Personal Identifiable Information loss
Dynamic Prompt Generation
Fully customized Retrieval Augmented Generation prompt generation capability to create and run dynamic generative AI prompts against proprietary data without code
LLM Performance Monitoring
Real-time monitoring of Large Language Model token usage, operational costs, and cost comparison capabilities across multiple Large Language Models
Standard contract
No
Customer reviews
reviewer2870895
Prompt-level AI visibility has transformed how I track brand presence and prioritize content work
Reviewed on Jul 13, 2026
Review provided by PeerSpot
What is our primary use case?
I mainly use Patronus AI for AI search visibility and brand monitoring, tracking how brands show up across AI search results. I work with HubSpot and use Patronus AI to set prompts such as 'What's the best CRM for small businesses?' or 'Best Salesforce alternatives,' then check AI search results to see if HubSpot is mentioned, where it ranks, who else shows up, and what sources are being cited. I track those changes over time and suggest content or data improvements to boost visibility.
What is most valuable?
The most useful aspects of Patronus AI are the AI search visibility tracking, competitor benchmarking, citation analysis, and prompt-level monitoring. I get a clear view of how I'm being presented to potential customers inside AI tools, which is super actionable. If I had to pick one, it would be prompt-level AI visibility tracking.
Prompt-level AI visibility tracking of Patronus AI grounds decisions in actual user language. I'm not guessing keywords; I'm seeing the exact prompts people would use and how the AI answers. That allows me to tweak content or messaging so it aligns with real queries, not assumptions, and it also helps me prioritize what to fix first.
Prompt-level AI visibility tracking helps me mainly in prioritization and speed. Patronus AI helps me waste way less time debating what content to create because I can see where I'm invisible and what to fix. It also makes reporting more data-driven and shows if I'm actually improving my AI presence over time.
What needs improvement?
I would love more actionable recommendations from Patronus AI, such as exactly what content to update. I would also appreciate deeper integrations with analytics and content tools, more granular reporting by market or segment, and proactive alerts when a competitor suddenly spikes.
Smoother exports and collaboration features would help Patronus AI, such as pushing insights straight into Jira or Slack, so it's easier to operationalize.
The missing pieces I mentioned regarding Patronus AI are integrations and more prescriptive guidance. Patronus AI is super for diagnosis but not as much for execution, and that's what stops it from being a 9 or 10 for me.
For how long have I used the solution?
I have been using Patronus AI deeply for about five years now.
What do I think about the stability of the solution?
From my user perspective, Patronus AI is stable. I did not run into frequent outages or anything that blocked day-to-day use.
What do I think about the scalability of the solution?
From an end-user's view, Patronus AI scaled fine for the use cases I saw. It handled more brands and prompts without getting unwieldy.
How are customer service and support?
From what I saw, Patronus AI support was good, responsive, and professional, but I did not need it very often.
Which solution did I use previously and why did I switch?
Before using Patronus AI, we had a patchwork of more manual checks, such as running prompts in ChatGPT or Perplexity , then tracking in spreadsheets and traditional SEO tools. We moved to a dedicated platform to centralize monitoring and cut manual effort.
How was the initial setup?
From a user standpoint, onboarding was straightforward, and I was able to get up to speed quickly.
What was our ROI?
I cannot share specific ROI numbers since I did not own that measurement. Qualitatively, the main return I saw from Patronus AI was time saved. Less manual monitoring and faster prioritization translated into smoother workflows rather than a directly measured headcount or cost number.
Which other solutions did I evaluate?
I looked around a bit before choosing Patronus AI but did not run a formal vendor bake-off. It was more a choice between sticking with manual workflows and a dedicated AI visibility platform.
What other advice do I have?
Rather than throw out numbers I cannot verify, I use Patronus AI more to guide which gaps to address and to track whether visibility improves over time, not to claim specific percentage lifts. The value is more about better decisions and clearer priorities.
In my experience, Patronus AI's accuracy and reliability of output is solid, but I still treat it as decision support, not ground truth. It is reliable enough to guide where to look and where to focus, but I always sanity-check the inputs.
Start with a clear goal when using Patronus AI, such as a short list of high-value prompts, and build from there. Focus on trends and prioritization, not single data points, and always sanity-check things before making big decisions.
Patronus AI is a solid tool and helpful for prioritization and staying data-informed.