Why Confident AI

Overview

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.

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.

Just Starting Out With LLM Evaluation?

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).

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.

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.