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Fiddler AI

  • What it is:Fiddler AI is an all-in-one AI Observability and Security platform that provides real-time monitoring, guardrails, root cause analysis, and governance for deploying AI agents, LLMs, and ML models in production.
  • Best for:Enterprise ML teams with regulated models, Teams deploying LLM agents, Organizations prioritizing responsible AI
  • Pricing:Starting from $0.002 per trace
  • Rating:82/100Very Good
  • Expert's conclusion:Fiddler AI is a production ready enterprise AI Observability and Security Platform for production deployment of LLM/AI agents that require Compliance and Reliability.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Fiddler AI and What Does It Do?

Fiddler AI is a Software Company that builds an AI Observability Platform to provide companies a way to see how their Machine Learning Models and Large Language Models (LLMs) are functioning; and to be able to analyze, explain and control them so they can govern their AI systems in a trustworthy way. The company was founded in 2018 in Palo Alto, CA and provides its products and services to enterprise level customers using its AI platforms in areas such as Government and Financial Services to help these companies manage their AI risk and improve the overall performance of their AI systems.

Active
📍Palo Alto, CA
📅Founded 2018
🏢Private
TARGET SEGMENTS
EnterprisesFinancial ServicesGovernmentData Science Teams

What Are Fiddler AI's Key Business Metrics?

📊
$63.2M
Total Funding
📊
$50M
Latest Funding
📊
5
Funding Rounds
💵
$12.2M
Revenue
🏢
86
Employees

How Credible and Trustworthy Is Fiddler AI?

82/100
Good

Fiddler AI is a leading company in the area of AI Observability with significant funding, experienced team members who have come from top technology companies, and a strong commitment to ensuring the responsibility of AI; however, there is very little public feedback on the company's products and services due to the lack of transparency regarding its metrics.

BREAKDOWN
Product Maturity85/100
Company Stability85/100
Security & Compliance80/100
User Reviews65/100
Transparency85/100
Support Quality75/100
TRUST SIGNALS
Well-funded with $63M total raisedTeam from Google, Facebook, MicrosoftMission-driven responsible AI focus

What is the history of Fiddler AI and its key milestones?

2018

Company Founded

In order to build trust and transparency into AI systems, Fiddler AI was established in Palo Alto, California to create an AI Observability Platform to measure, evaluate and optimize the performance and behavior of AI systems.

2023

ML Performance Management Platform Launch

To promote transparency and accountability within AI systems, Fiddler AI has released a new AI Observability Platform which includes the integration of Model Explainability to enable organizations to apply Responsible AI Governance to their AI Systems.

2024

Series B - II Funding

Fiddler AI has received its most recent round of financing in the amount of $50 Million, and this round of financing represents one of five rounds of financing that the company has received in total, with all five rounds representing a total investment of $63.2 Million.

What Are the Key Features of Fiddler AI?

✨
AI Model Monitoring
Fiddler AI uses continuous monitoring to continuously monitor the performance of its customers' Machine Learning Models and LLMs in order to detect any issues related to the performance of the models, and to detect any Data Drift.
✨
Explainable AI
Fiddler AI provides its customers with Model Explainability capabilities to help its customers understand the reasons behind its customers' Machine Learning Models' predictions, and to identify the source(s) of any potential biases or errors.
✨
Bias Detection
Using the Model Explainability capabilities of its AI Observability Platform, Fiddler AI enables its customers to analyze their Machine Learning Models for Fairness and Bias to ensure that its customers' AI systems produce Equitable Outcomes across different Demographics.
✨
AI Governance
Fiddler AI provides its customers with end-to-end Risk Management and Compliance capabilities to support the responsible deployment of its customers' AI Systems.
✨
Analytics Dashboard
Fiddler AI provides its customers with visual analytics capabilities to enable its customers to analyze the performance of their Machine Learning Models, to validate their Machine Learning Models, and to manage the lifecycle of their Machine Learning Models.
✨
Model Validation
Prior to deploying their AI Solutions in Production, and after deploying their AI Solutions in Production, Fiddler AI enables its customers to validate and test their AI Solutions using the various testing and validation tools provided by Fiddler AI.

What Technology Stack and Infrastructure Does Fiddler AI Use?

Infrastructure

Cloud-based multi-region deployment

Technologies

PythonMachine LearningCloud Infrastructure

Integrations

ML PipelinesCloud PlatformsData Warehouses

AI/ML Capabilities

Advanced ML observability with explainable AI techniques, bias detection algorithms, and LLM monitoring capabilities

Inferred from product focus on ML observability and industry standards

What Are the Best Use Cases for Fiddler AI?

Enterprise Data Science Teams
After its customers deploy their Machine Learning Models in Production, Fiddler AI enables its customers to continuously monitor their Machine Learning Models in Production to ensure that their Machine Learning Models continue to function accurately and reliably at scale.
Financial Services AI Teams
Using the Explainable AI and Bias Detection capabilities of its AI Observability Platform, Fiddler AI enables its customers to implement Explainable AI and Bias Detection to support the Regulatory Compliance and Risk Management requirements of its customers' AI Systems.
Government AI Programs
Using the comprehensive governance tools of its AI Observability Platform, Fiddler AI enables its customers to achieve Transparency and Accountability in Public Sector AI Deployments.
NOT FORSmall Startups
Because of its enterprise-grade features and functionality, Fiddler AI's AI Observability Platform may offer more than what some of its smaller-scale customers need and/or can afford to purchase and utilize.
NOT FORNon-ML Developers
The use of Fiddler AI's AI Observability Platform requires specialized knowledge and skills in Machine Learning; therefore, the utilization of Fiddler AI's AI Observability Platform may not be appropriate for general software developers who do not possess the required knowledge and skills in Data Science.

How Much Does Fiddler AI Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Developer$0.002 per traceEverything in Free, plus unified AI observability including tests and experiments for agentic and predictive systems, custom evaluators, bring your own judge, visualization-driven insights, role based access control and SSO, SaaS deploymentOfficial pricing page
LiteUsage-based (data ingested, models)Core model monitoring and explainable AI capabilities for small to mid-sized ML teams. Includes 1 model, 0.5 GB data/month in AWS Lite version. Annual commitment requiredOfficial blog and AWS Marketplace
StandardUsage-based (data ingested, models, explanations, retention)Enterprise-level capabilities including security compliance, AI fairness assessment, advanced explainability, Virtual Private Cloud (VPC) deployments, add-ons like GPU accelerated explanations and expert supportOfficial blog
BusinessCustom usage-basedAdvanced model analytics, fairness and bias assessment, enhanced security with RBAC and SSO, dedicated Customer Success Manager, engineering and data science servicesThird-party analysis
PremiumCustom usage-basedSaaS and On-Premise deployment options, white-glove support, customized onboarding, solution success, dedicated communication channels for business-critical modelsThird-party analysis
Developer$0.002 per trace
Everything in Free, plus unified AI observability including tests and experiments for agentic and predictive systems, custom evaluators, bring your own judge, visualization-driven insights, role based access control and SSO, SaaS deployment
Official pricing page
LiteUsage-based (data ingested, models)
Core model monitoring and explainable AI capabilities for small to mid-sized ML teams. Includes 1 model, 0.5 GB data/month in AWS Lite version. Annual commitment required
Official blog and AWS Marketplace
StandardUsage-based (data ingested, models, explanations, retention)
Enterprise-level capabilities including security compliance, AI fairness assessment, advanced explainability, Virtual Private Cloud (VPC) deployments, add-ons like GPU accelerated explanations and expert support
Official blog
BusinessCustom usage-based
Advanced model analytics, fairness and bias assessment, enhanced security with RBAC and SSO, dedicated Customer Success Manager, engineering and data science services
Third-party analysis
PremiumCustom usage-based
SaaS and On-Premise deployment options, white-glove support, customized onboarding, solution success, dedicated communication channels for business-critical models
Third-party analysis

How Does Fiddler AI Compare to Competitors?

FeatureFiddler AIArize AIWeights & BiasesTruEra
Core FunctionalityModel monitoring, explainability, fairnessMonitoring, drift detectionExperiment tracking, monitoringTesting, validation
AI Safety/GovernanceYes (fairness, guardrails)PartialPartialPartial
LLM ObservabilityYes (traces, evaluators)YesYesLimited
Pricing (starting)Usage-based $0.002/trace$0.30/GB$50/user/moCustom
Free TierYes (Developer $0.002/trace)YesYesTrial
Enterprise Features (SSO, VPC)Yes (Standard+)YesYesYes
API AvailabilityYesYesYesYes
Integration CountMultiple ML frameworks20+50+Limited
Support OptionsDedicated (Business+)EnterprisePriorityEnterprise
Security CertificationsSOC2, GDPR (enterprise)SOC2SOC2GDPR
Core Functionality
Fiddler AIModel monitoring, explainability, fairness
Arize AIMonitoring, drift detection
Weights & BiasesExperiment tracking, monitoring
TruEraTesting, validation
AI Safety/Governance
Fiddler AIYes (fairness, guardrails)
Arize AIPartial
Weights & BiasesPartial
TruEraPartial
LLM Observability
Fiddler AIYes (traces, evaluators)
Arize AIYes
Weights & BiasesYes
TruEraLimited
Pricing (starting)
Fiddler AIUsage-based $0.002/trace
Arize AI$0.30/GB
Weights & Biases$50/user/mo
TruEraCustom
Free Tier
Fiddler AIYes (Developer $0.002/trace)
Arize AIYes
Weights & BiasesYes
TruEraTrial
Enterprise Features (SSO, VPC)
Fiddler AIYes (Standard+)
Arize AIYes
Weights & BiasesYes
TruEraYes
API Availability
Fiddler AIYes
Arize AIYes
Weights & BiasesYes
TruEraYes
Integration Count
Fiddler AIMultiple ML frameworks
Arize AI20+
Weights & Biases50+
TruEraLimited
Support Options
Fiddler AIDedicated (Business+)
Arize AIEnterprise
Weights & BiasesPriority
TruEraEnterprise
Security Certifications
Fiddler AISOC2, GDPR (enterprise)
Arize AISOC2
Weights & BiasesSOC2
TruEraGDPR

How Does Fiddler AI Compare to Competitors?

vs Arize AI

Both Fiddler and Arize emphasize fairness in machine learning, but Arize also focuses on detecting data drift and measuring model performance, while Fiddler focuses more on the explainability of artificial intelligence and fair assessment of artificial intelligence and the observation of large language models.

Fiddler allows users to separate their pricing for monitoring, explaining and assessing fairness separately, which provides much greater pricing flexibility compared to W&B's seat based pricing model.

vs Weights & Biases (W&B)

While Fiddler is focused primarily on the production observation of machine learning models, and the observation of large language models, W&B is much more well-rounded and focused on all aspects of a machine learning workflow, including experimentation, training, and deployment.

TruEra provides an ML testing framework that includes fairness and transparency while Fiddler provides a full observability platform that includes monitoring, explanations, and fairness assessments. In addition to being an observability platform, Fiddler provides many additional enterprise-grade features such as VPC, SSO and supports large language models, while TruEra appeals to developers due to its open-source roots and is particularly popular among teams developing and deploying ML testing frameworks.

vs TruEra (TruLens)

Fiddler is a more comprehensive and robust solution for responsible artificial intelligence governance in production environments, however, Fiddler uses a usage-based pricing model that may be less predictable than Arize's tiered pricing model.

WhyLabs provides lightweight monitoring-as-a-service while Fiddler provides deep explainability and governance features. Because WhyLabs' pricing is based on the volume of predictions made by the model, it may not be as well-suited to teams with variable or unpredictable workloads, whereas Fiddler charges per unit of data ingested into the system and therefore is able to accommodate those types of workloads.

vs WhyLabs

W&B is significantly more advanced in terms of experiment tracking compared to Fiddler, because W&B tracks all aspects of the machine learning workflow, from experimentation through to deployment, whereas Fiddler is focused primarily on production observability and model explainability, as well as agentic systems.

For teams that prioritize AI safety and governance, Fiddler is likely a better choice, while Arize is likely to be a better choice for teams that are primarily interested in monitoring the performance of their models.

What are the strengths and limitations of Fiddler AI?

Pros

  • Teams conducting research and/or experimentation are likely best served using W&B, while teams that have moved into production and require a more complete and robust governance and explanation framework would be best served by using Fiddler.
  • Teams that require enterprise-level production monitoring are likely best served using Fiddler, while teams that are testing-focused are likely best served using TruEra.
  • Teams that need comprehensive observability are likely best served using Fiddler, while teams that simply want to perform lightweight monitoring are likely best served using WhyLabs.
  • Fiddler is transparent about how much it costs to use their product and only charges customers based on how much data they ingest into the system and how many models they choose to monitor.
  • Unlike other products that charge flat fees, regardless of how much data you ingest into the system or how many models you choose to monitor, Fiddler provides decoupled capabilities for monitoring, explaining and assessing fairness in models and charges each capability separately.
  • Fiddler provides strong support for observing large language models, including traces, custom evaluators, and agentic systems, and provides a strong platform for monitoring and explaining complex ML models.
  • Scalable metrics - data ingestion directly relates to actual model complexity and utilization

Cons

  • Unpredictable pricing - the consumption model makes it challenging to forecast yearly budgets
  • Annual contract requirement - no month-to-month flexibility despite the usage-based metric of consumption
  • A complex calculator is necessary - requires an estimate of data ingestion and traces upfront
  • More expensive for explanations - The same explanation on a GPU-accelerated model is as much as an additional add-on
  • Little value for free tier - The Developer plan still charges $0.002 per trace
  • Extra for data retention - Only applicable to managed cloud deployments
  • Enterprise feature tier locked - Basic Teams are missing out on fairness and advanced security

Who Is Fiddler AI Best For?

Best For

  • Enterprise ML teams with regulated models — Fairness and compliance features, VPC deployment and dedicated support, all provide assurance that governance requirements will be fulfilled
  • Teams deploying LLM agents — Unified observability for agentic systems with traces, custom evaluators, and visualization insights
  • Organizations prioritizing responsible AI — Focus on explainability, fairness, and trustworthy model outcomes from a mission-driven perspective
  • Teams with variable ML workloads — Usage-based pricing scales to actual data ingestion instead of fixed seats or predictions
  • Companies needing multi-deployment options — SaaS, VPC, and On-Premise flexibility without pricing penalties across models

Not Suitable For

  • Small teams with fixed budgets — Usage-based pricing is unpredictable; Consider using Arize or WhyLabs for more defined tiers
  • Experiment-only ML teams — Too much overhead for the research phase; Better suited for Weights & Biases for tracking experiments
  • Solo developers or hobbyists — The even Developer tier has a charge per trace; Open source alternatives such as TruLens would be preferable
  • Teams needing simple monitoring only — Too costly for simple needs; WhyLabs or Grafana ML plugins are more cost effective

Are There Usage Limits or Geographic Restrictions for Fiddler AI?

Data Ingested
Primary pricing metric - size of predictions, metadata, baselines, model artifacts
Models Monitored
Priced per model; Lite includes 1 model
Explanations
Number of model inferences explained; additional cost
Data Retention
Number of months raw data retained; managed cloud only
Annual Commitment
Pre-commit to monthly volume for entire year
Lite Data Limit
0.5 GB data/month (AWS Marketplace Lite version)
No LLM in Lite
AWS Lite version excludes LLM functionality
Deployment Options
SaaS (all plans), VPC/On-Prem (higher tiers only)

Is Fiddler AI Secure and Compliant?

SOC 2 ComplianceEnterprise-level security compliance included in Standard plan and above
Role-Based Access Control (RBAC)Granular permissions with role management; Developer plan and above
Single Sign-On (SSO)Enterprise authentication support; Developer plan includes SSO
Virtual Private Cloud (VPC)Private deployment option for Standard plan and above
GDPR ComplianceData protection regulations met for global customers
Data EncryptionProduction data protected at rest and in transit (enterprise features)
Audit CapabilitiesMonitoring and explanation logs for compliance and troubleshooting
On-Premise DeploymentPremium plan option for complete data sovereignty control

What Customer Support Options Does Fiddler AI Offer?

Channels
help@fiddler.ai for general support, security@fiddler.ai for security concerns, sales@fiddler.ai for salesFiddler Community Slack, #fiddler-guardrails-support channel for feedback and feature requestsIn-app Contact Support for paid subscription and trial users24/7 self-service at docs.fiddler.aiTier 1 support via AWS, escalates to Fiddler as Tier 2
Hours
24/7 documentation access; email/Slack business hours typical; AWS support 24x7x365
Response Time
Not publicly specified; fair usage policy applies to paid support
Satisfaction
Not available from public sources
Specialized
Guidance on features, bug confirmation, workarounds for paid users
Business Tier
Unlimited dedicated support for paid subscriptions/trials with fair usage policy
Support Limitations
•Free users limited to community Slack, documentation, GitHub issues, and feedback portal - no dedicated support
•Paid support subject to fair usage policy; excessive requests may be reviewed
•No phone support mentioned

What APIs and Integrations Does Fiddler AI Support?

API Type
REST API with OpenAPI specifications (inferred from documentation structure)
Authentication
Personal Access Tokens via Credentials settings; LLM provider API keys
Webhooks
Supported for alerts - Slack, Microsoft Teams, custom endpoints with severity mapping
SDKs
Not mentioned; Python/JavaScript likely via standard REST clients
Documentation
Comprehensive at docs.fiddler.ai with LLM Gateway, Settings, and Guardrails references
Sandbox
Fiddler Free Guardrails available for testing
Integrations
PagerDuty, Slack, Microsoft Teams, LLM providers (OpenAI, Anthropic, Gemini, Fiddler)
Email Integration
AWS SES or custom SMTP server configuration
Use Cases
Alert notifications, LLM evaluations, custom evaluators, content analysis, monitoring

What Are Common Questions About Fiddler AI?

Both paid and trial users receive dedicated support through in-app tickets at help@fiddler.ai. The free users receive community Slack, documentation and GitHub issues. AWS Marketplace provides Tier 1 Support with Fiddler Escalation.

Currently available only in English. The company is currently evaluating additional languages due to user feedback.

Utilize the Settings section of the LLM Gateway (OpenAI, Anthropic, etc.), PagerDuty, webhooks (Slack/Teams/custom), and email (SES/SMTP) as shown in the Fiddler documentation, which has complete details of how to configure these items.

Fiddler Free Guardrails does have some basic protections. A full observability platform will require an active paid subscription.

Fiddler observes what decisions are being made by its agents, ensures that hallucination/bias/data leak events do not occur, enforces the guardrails, and links together technical metrics such as NPS and resolution time with business KPIs.

If you need assistance with Fiddler, please join our Fiddler Community Slack (#fiddler-guardrails-support) or utilize the in-app feedback mechanisms provided to us. We also send out product updates via newsletters.

Fiddler provides audit trails that can be used to provide evidence for GDPR, CCPA, HIPAA, NAIC compliance, and is able to give your organization complete visibility into what your agents are doing in real-time along with a full view of all guardrails.

Please visit docs.fiddler.ai to view the documentation. For demo requests, contact sales@fiddler.ai. For ease of use with support, Fiddler AI can be easily deployed from AWS Marketplace.

Is Fiddler AI Worth It?

Fiddler AI is a mature enterprise-grade platform for AI observability, security, and governance, and is very well suited for agentic systems and customer-facing LLM applications. Due to comprehensive monitoring, real-time guardrails, and production-ready integrations, it is well-suited for organizations that want to deploy responsible AI at scale.

Recommended For

  • Enterprises using customer-facing AI agents and LLM applications.
  • Teams of ML/AI developers who need to monitor their AI models in production and debug them.
  • Teams requiring audit trail capabilities due to compliance regulations (GDPR, HIPAA, etc.).
  • Teams required to manage multiple LLM providers and complex agent work flows.

!
Use With Caution

  • Teams of one to three people. The focus of enterprise solutions may be too much for smaller teams, both in terms of cost and scope.
  • Users who only have access to the free tier. In this case, they can only use the basic Guardrails feature without having access to the full observability feature set.
  • Non-English speaking users. Currently, Guardrails only supports English.

Not Recommended For

  • Individuals and hobbyists. Enterprise solutions are typically priced in a manner that individual developers/hobbyist cannot afford, and are usually far too complex for individuals.
  • Developers/users only interested in testing simple models. While Fiddler AI can certainly help with model testing, its primary focus is on providing tools and features to support development and pre-deployment testing, not just post-deployment.
  • Small businesses (SMBs) that are budget constrained and/or do not have any regulatory compliance issues.
Expert's Conclusion

Fiddler AI is a production ready enterprise AI Observability and Security Platform for production deployment of LLM/AI agents that require Compliance and Reliability.

Best For
Enterprises using customer-facing AI agents and LLM applications.Teams of ML/AI developers who need to monitor their AI models in production and debug them.Teams requiring audit trail capabilities due to compliance regulations (GDPR, HIPAA, etc.).

What do expert reviews and research say about Fiddler AI?

Key Findings

Fiddler AI offers an Enterprise Grade AI Observability and Monitoring solution with built-in Security and Integration (with PagerDuty, Slack, LLM Providers) for Agentic Systems and LLM Applications. Offers multiple support levels (Free Community, Paid Dedicated).

Data Quality

Good - detailed documentation and product pages available. Limited public info on pricing, specific SLAs, customer satisfaction ratings, and API specs. No G2/Capterra reviews in results.

Risk Factors

!
Enterprise Pricing requires Sales Contact - Not Publicly Available
!
Limited Free Tier compared to Paid Features
!
Only English Guardrails available for Global Adoption
!
No Visible API Rate Limits / SLA Details Publicly Available
Last updated: February 2026

What Are the Best Alternatives to Fiddler AI?

  • •
    Weights & Biases (W&B Weave): Provides a solid ML Observability Platform for Experiment Tracking and LLM Evaluation. Ideal for Research/Development Workflows; Less focused on Agentic System. Ideal for Data Science Teams. (wandb.ai)
  • •
    LangSmith (LangChain): Observability of LLM Applications are Tied to the LangChain Ecosystem. Developer-Friendly but Ecosystem-Specific. Ideal for LangChain Users Building LLM Apps. (langchain.com/langsmith)
  • •
    Honeycomb: A general-purpose Observability Platform with AI/ML Support. Broader Infrastructure Focus than Specialized for LLM/AI Agent Monitoring. Ideal for Unified Observability Stacks. (honeycomb.io)
  • •
    TruEra (TruLens): An Open-Source LLM Evaluation Framework with Enterprise Options. Strong Custom Evaluations, Lighter Production Monitoring. Ideal for Evaluation-Focused Teams. (truera.com)
  • •
    Arize AI: An ML Observability Platform with robust Production Monitoring Capabilities. Broader ML Focus than Just LLM/Agent. Ideal for Hybrid Teams using Traditional ML and GenAI. (arize.com)

What Are Fiddler AI's Evaluation Metrics?

<100 ms
Trust Score Response Time
50 %
LLM Evaluation Accuracy Improvement
Thousands concurrent
Parallel Test Case Processing

What Testing Capabilities Does Fiddler AI Offer?

A/B Testing

Evaluate Different Prompt Strategies and Model Versions Side by Side

Regression Testing

Verify that Updates to Models Do Not Negatively Impact Critical Capabilities

Data Drift Detection

Monitor Changes to Distributions of Data That Are Affecting Performance of Models

Bias and Fairness Analysis

Detect Demographic Biases and Validate Fairness of Outputs of Models

Data Integrity Testing

Detect Missing Data, Range Violation, and Type Mismatch Issues in Data Used in Models

Class Imbalance Detection

Identify changes in the low frequency of predictions

Model Validation

Evaluate how well a model is working before it is deployed for use by the public

How Does Fiddler AI's Benchmark Support Compare?

Evaluation DimensionCategorySupported
FaithfulnessLLM QualityYes
LegalityContent SafetyYes
Toxicity DetectionHarmful ContentYes
Jailbreak DetectionSecurityYes
PII & Data LeakagePrivacyYes
Custom EvaluatorsUse Case SpecificYes

What Model Compatibility Does Fiddler AI Support?

LLM ApplicationsAI AgentsMachine Learning ModelsComputer Vision ModelsGenerative AIAny LLM ProviderCustom ModelsAgentic Frameworks

What Is Fiddler AI's Evaluation Modes?

Evaluation Pattern
LLM-as-a-Judge with automated quality assessment
Test Execution
Systematic test suites with real-world scenarios
Comparison Approach
Side-by-side experiment analysis
Ground Truth Updates
Delayed, asynchronous label updates

How Does Fiddler AI Ensure Safety Through Testing?

Toxicity Detection

Detect hate speech, racist comments, sexism, violence, and harassment

Jailbreak Testing

Identify prompt injections and adversarial attack attempts

Harmful Content Detection

Flag sexual, unethical or harmful generation of responses

LLM Guardrails

Moderate both the prompts that users input and the responses generated by the model using predefined levels of trust

Security Threat Protection

Protect against prompt injections and adversarial attacks

Image Security Monitoring

Continuously monitor image models to detect threats

What Is Fiddler AI's Ci Cd Integration?

API Access
REST API and Python SDK
Deployment
Plug-in integration with enterprise infrastructure
Alerting
Real-time alerts via Slack, Email, Webhook
Framework Support
Framework-agnostic compatibility
Data Handling
Enterprise security - data stays within environment
Scalability
Large-volume data ingestion and parallel evaluation

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