Turn live traces into test cases, validate with evals, and catch vulnerabilities before they ship.
Align every team to the same evals and quality bar — no matter who ships the release.
“We hit a point where every AI team was building their own eval stack. That’s fine for one product. With five, ten, fifteen AI initiatives across the portfolio, it’s never going to live up to our high standards of AI governance.”
Purpose built for industries where a perfectly functional AI is not good enough.
Attackers manipulate agent goals, plans, or decision paths through direct or indirect instruction injection, causing agents to pursue unintended or malicious objectives.
“Confident AI increased our speed to market by 200%. For us, compliance and trust aren’t optional—they’re required. Confident AI helps us deliver both.”
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Improving your score from 670 to 700 is achievable. A few strategies to start with:
“Before Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.”
Every part of Confident AI is exposed as an API. Version prompts, build datasets, ingest traces, ship custom dashboards — wire it into whatever your team already runs on.
1from deepeval.prompt import Prompt2from deepeval.prompt.api import PromptMessage3 4prompt = Prompt(alias="support-agent-v2")5 6# Push to Confident AI, synced with your GitHub repo7prompt.push(8 messages=[9 PromptMessage(10 role="system",11 content="You are an AI support agent with access to tools. "12 "Use them to look up orders, process refunds, and resolve issues. "13 "Always verify the customer's identity before making changes.",14 ),15 ]16)17 18# Pull a specific version in production19prompt.pull(version="latest")SDKs in Python, Typescript; 20+ integrations, including OpenAI, LangGraph, Opentelemetry, and tons of more LLM gateways.
Join the largest and fastest growing community on AI evaluation.
FinomBefore Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.
Confident AI saves us 480+ hours of manual AI evaluation every month — and gives us the data to defend every quality decision in front of engineering, product, and leadership.
Confident AI gave our team one place to turn production failures into datasets, align metrics, and keep regressions out of releases without waiting on custom engineering work.
HumachWe run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools.
Thanks to Confident AI, we were able to move to a fine-tuned model and cut our LLM costs by 80%. This opens up whole new use cases now to generate better output with more targeted LLM calls.
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