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About

Confident AI offers an open-source package called DeepEval that enables engineers to evaluate or "unit test" their LLM applications' outputs. Confident AI is our commercial offering and it allows you to log and share evaluation results within your org, centralize your datasets used for evaluation, debug unsatisfactory evaluation results, and run evaluations in production throughout the lifetime of your LLM application. We offer 10+ default metrics for engineers to plug and use.

About

AI agents fail silently in production. Wrong answers, broken loops, cost spikes, behavior drift after a prompt change, and no stack trace to explain why. Netra is the single platform to trace, evaluate, simulate and security test your agents. Built for text, voice, image and video agents. SOC2 Type II certified. GDPR and HIPAA compliant. US and EU data residency. Integrates with: LangChain, LangGraph, CrewAI, LlamaIndex, OpenAI, Anthropic, Gemini, AWS Bedrock, and 30+ more.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Supported
Chromebook Not Supported

Audience

Enterprises searching for a solution to evaluate LLMs in production

Audience

Teams building AI agents and Agentic AI products

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

$39/month
Free Version Supported
Free Trial Supported

Pricing

$39/month
Free Version Not Supported
Free Trial Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 4.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • ==Simulation mode lets you stress-test agents before production. You can spin up multi-turn conversations with defined personas and goals, auto-evaluated against fact-checking criteria you set. Instead of manual testing or hoping users find the edge cases, you run realistic scenarios and see where agents fail. Saves weeks of "what if" testing. Evaluation framework is actually repeatable. Not just pass/fail. You're measuring model quality, reasoning accuracy, tool correctness, output reliability—with metrics that stick across runs. That means you can compare versions, track improvements, and catch regressions before they hit users. Alerting catches problems you'd otherwise miss. Cost spikes, performance drops, safety violations, weird agent behavior—real-time notifications instead of discovering issues in production. That's table stakes for shipping anything at scale. Works across the whole ecosystem. OpenTelemetry standards, integrations with OpenAI, Claude, Anthropic, vector databases, LangChain, LlamaIndex. Not locked into one vendor. Multi-tenancy for SaaS applications. Voice traces for voice pipelines too, if that's your stack. Netra handles both text and voice traces end-to-end. Text captures LLM calls, tool executions, vector searches. Voice pipelines trace the full chain: speech-to-text, reasoning, text-to-speech. One platform for observing how your agents think and communicate, no matter the modality. That's rare.

Cons

  • SDK integration is non-negotiable overhead. You can't just drop this in and observe magically. Netra requires explicit instrumentation across your codebase. Multi-language support helps, but you're still looking at integration work across services. That's friction most teams don't have budget for on day one. Less public mindshare than competitors. Datadog, New Relic, LangSmith get more air time. Netra doesn't have the same community gravity or case study library. Fewer public comparisons, less blog coverage, smaller forum. That means fewer answers when you hit problems and harder time recruiting help from people who already know the tool. The documentation is excellent and so is the customer support

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Confident AI
Founded: 2023
United States
www.confident-ai.com

Company Information

Netra
Founded: 2025
getnetra.ai/

Alternatives

Alternatives

Traccia

Traccia

Algen AI
Gru

Gru

Gru.ai

Categories

AI Development Supported
AI Testing Tools Supported
Unit Testing Supported

Categories

Integrations

CrewAI Not Supported
LangChain Not Supported
LlamaIndex Not Supported
OpenTelemetry Not Supported

Integrations

CrewAI Supported
LangChain Supported
LlamaIndex Supported
OpenTelemetry Supported
Claim Confident AI and update features and information
Claim Confident AI and update features and information
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