The All-In-One LLM Evaluation Solution

Confident AI is an evaluation-first platform for testing LLM applications and replaces a lot if not all of your tedious manual LLM evaluation workflows / any existing solutions you may already be using.

A few reasons why engineering teams choose Confident AI:

Built on DeepEval, the most adopted open-source LLM evaluation framework (10M+ evals per week, 40+ metrics for all use cases)
Every feature is purpose-built for LLM evaluation workflows — improve metrics, datasets, models, or prompts
Never get stuck — built by the creators of DeepEval, you won’t run into issues with more complicated evals when compared to generic platforms that treat eval as an afterthought

DeepEval vs Confident AI

“Oh, so DeepEval is Confident AI’s biggest competitor?”

DeepEval is the open-source LLM evaluation framework, and while DeepEval powers the metrics that are used to populate evaluation results on Confident AI, they are very different products.

DeepEval is like Pytest for LLMs - it runs in the terminal through a Python script, you get to see the results, but nothing else happens afterwards.

Confident AI created and owns DeepEval.

With Confident AI, you’ll have a centralized place to manage testing reports, catch regressions before your users do, auto-optimize on prompts you version on the platform (based on eval results), trace and monitor LLM interactions in production, and collect human feedback from either end users or internal reviewers just to make better data driven decisions apart from relying on DeepEval’s LLM-as-a-judge metrics.

DeepEval

Confident AI

Open-source
Runs evals locally
No data persistence & UI
No testing report sharing
Hard for A|B testing
No real-time evals
No observability and tracing
Red teaming available in DeepTeam
Community support

100% integrated with DeepEval
Runs evals locally and on the cloud
Manage and A|B test prompts
Curate and annotate datasets
Data persistence with sharable testing reports
Accessible for all stakeholders in your organization
Real-time online evals and performance alerting
LLM observability with tracing
Collect end-user and internal feedback
Email, private, and live video call support

Just Starting Out With LLM Evaluation?

💡

Confident AI takes on average 10 minutes to setup

For those that have yet to start using any LLM evaluation/observability platform, Confident AI will help you build the best version of your LLM application by:

Regression testing LLM apps for quality
Eliminate manual CSV workflows for analyzing and sharing testing reports
Version and optimize prompts
Avoid spreadsheets to annotate datasets
Streamline collaboration between engineering and non-engineering teams
Gain real-time visibility into LLM app performance in production
Use production data to make datasets more robust
Collect human feedback from users and internal reviewers

Every feature is designed to either enhance your evaluation results — so you can iterate faster with more valid data, or directly improve your LLM application (through model and prompt suggestions).

Self-Maintained Methods

Confident AI

Hours spent manually reviewing outputs
Constantly recreating test cases from scratch
No way to track if quality drops over time
Hard to share insights with team members
Difficult to justify model or prompt changes
Built your own dashboard

Save countless hours on LLM evaluation with automated testing
Build a reusable test suite that grows with your application
Catch quality drops before your users do
Create shareable testing reports that anyone can understand
Make data-driven decisions about model and prompt changes
Turn user feedback directly into test cases
Identify exactly which model or prompt works best for your use case
Confidently ship LLM features knowing they've been thoroughly tested
Detect and fix hallucinations before deployment
Show stakeholders clear evidence of LLM performance improvements

What If I’m Already Using Another Solution?

If you decide Confident AI is a better fit for you, switching to Confident AI is an extremely easy process. Common reasons why users switch to us:

Whatever you’re using does not work (literally)
Your provider is trying to force you into an annual contract
Evaluation features are minimal (limited metrics, poor support for chatbots and agents, etc.)
Does not cover the workflows of non-technical team members (domain experts needing to review testing data, external stakeholders, legal compliance people)
You’d like an all-in-one solution with safety testing features as well (red teaming, guardrails)
Frustration with customer support
You like reading our docs more 😉

Note

The most common solutions users switch from to Confident AI is Arize AI, Langsmith, Galileo, and Braintrust.

On the contrary, sometimes what you’re using works completely fine, and it’s true that some evaluation needs can be satisfied by LLM observability-first solutions. But as your LLM system matures, issues like poor test coverage, unreliable metrics, and scaling to more LLM evaluation needs start to surface, especially with tools that don’t specialize in evaluation and OWN their eval algorithms.

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Confident AI started with DeepEval, meaning that you’ll know for sure that whatever metrics you decide to use is the best out there.

Common problems you’ll face:

Poor LLM test coverage
“LLM-as-a-judge” metrics that aren’t repeatable, with no clear path to customization
Does not extend into safety testing (red teaming and guardrails) for things like bias, PII leakage, misinformation, etc.
No clear ownership or expertise in LLM evaluation means you’re on your own for any evaluation related problems, even for things as simple as coming up with an evaluation strategy

Confident AI is built by the creators of DeepEval, so unlike general-purpose platforms, we’re here to make sure you never hit any bottlenecks.