Confident AI - The AI Quality Platform (original) (raw)
Turn live traces into test cases, validate with evals, and catch vulnerabilities before they ship.
THE ROI
One eval standard. Enforced across every team.
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.”
HOW TEAMS WORK
Where product, QA, and engineering align.
One platform that gives engineers, product owners, and QA teams a shared source of truth.
LLM Tracing
Trace UUID 6d63ad3c-8083-fa75-93dd-82e36b52996a
ics_orchestratorAGENT23.52s
ops_analyst_agentAGENT10.41s
gen_dynamics_knowledgeFUNC2.10s
gen_response_w_tracingLLM8.31s
ops_report_formatterFUNC12.84s
INPUT
How can I improve my credit score from 670 to 700?
OUTPUT
Improving your score from 670 to 700 is achievable. A few strategies to start with:
- Check Your Credit Report — Pull a free copy from each of the three major bureaus.
- Pay Bills On Time — Payment history is the largest factor in your score.
“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.”
WHO WE SERVE
For AI that has to be safe. Not just useful.
Purpose built for industries where a perfectly functional AI is not good enough.
“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.”
THE PLATFORM
Built for every step of the AI lifecycle.
Alert on monitored traces
Inspect every trace in production, monitor quality and latency over time, and get notified immediately when regressions or incidents occur.
Dataset auto-curation
Turn observability traces into evaluation datasets automatically, then auto-categorize failures and edge cases so dataset operations scale with your product.
Postman for AI apps
Let product owners and non-engineers call your AI app directly over HTTP and streaming endpoints, without waiting on engineering or relying on mock single-prompt tests.
Chat simulations
Evaluating multi-turn chatbots bottlenecks on manually prompting realistic conversations. Simulate thousands of conversations in 10 minutes to test behavior before release.
AI risk assessments
In a regulated industry? Confident AI centralizes red teaming workflows so you catch risks before users do, with PDF ready assessment reports you can share with stakeholders.
Git-based prompt versioning
Manage prompts with a git-based branching workflow synced to your codebase. Teams can work in parallel, enforce merge permissions, and gate merges with eval results.
ENTERPRISE
The security posture your compliance team wants.
HIPAA, SOCII COMPLIANT
Our compliance standards meets the requirements of even the most regulated healthcare, insurance, and financial industries.
MULTI-DATA RESIDENCY
Store and process data in the United States of America (North Carolina) or the European Union (Frankfurt).
RBAC AND DATA MASKING
Our flexible infrastructure allows data separation between projects, custom permissions control, and masking for LLM traces.
99.9% UPTIME SLA
We offer enterprise-level guarantees for our services to ensure mission critical workflows are always accessible.
ON-PREM HOSTING
Optionally deploy Confident AI in your cloud premises, may it be AWS, Azure, or GCP, with tailored hands-on support.
AUTOMATIONS
APIs for the entire pipeline.
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 Prompt
2from deepeval.prompt.api import PromptMessage
3
4prompt = Prompt(alias="support-agent-v2")
5
6# Push to Confident AI, synced with your GitHub repo
7prompt.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 production
19prompt.pull(version="latest")
INTEGRATION
Stay in your stack.
We'll meet you there.
SDKs in Python, Typescript; 20+ integrations, including OpenAI, LangGraph, Opentelemetry, and tons of more LLM gateways.
pip install deepeval
OpenAI AgentsLlamaIndexLangGraphPydantic AICrew AIOpenTelemetryOpenAILangChainVercel AI SDKAgent CoreLiteLLMPortkeyspan_01trace_01trace_02span_02span_03span_04Prompt Leakage6%Goal Theft7%PII Leakage4%Excessive Agency3%Misinformation5%Bias2%OpenAI AgentsLlamaIndexLangGraphPydantic AICrew AIOpenTelemetryOpenAILangChainVercel AI SDKAgent CoreLiteLLMPortkeyspan_01trace_01trace_02span_02span_03span_04Prompt Leakage6%Goal Theft7%PII Leakage4%Excessive Agency3%Misinformation5%Bias2%
COMMUNITY
Join the largest and fastest growing community on AI evaluation.
TESTIMONIALS
Trusted by companies that take AI seriously.
Finom
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.
Igor Kolodkin,Head of AI Quality, Finom
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.
Anoop Mahajan,Director of QA, Amdocs
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.
SD
Senior Director of Engineering,Fortune 500 medical device company
Humach
We 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.
Sean Austin,Chief AI Officer, Humach
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.
John Lemmon,AI Lead, Supernormal
FAQ
Have a Question?
Checkout our FAQs below, or talk to a human. They won't hallucinate.
Confident AI is the AI quality platform built by the creators of DeepEval. It gives engineering, QA, and product teams a single place to evaluate, observe, and improve LLM applications — from prototyping through production.
DeepEval is our open-source evaluation framework for running LLM tests locally or in CI. Confident AI is the cloud platform that layers on top — adding collaboration, dataset management, tracing, real-time monitoring, and dashboards so the whole team can work together.
Yes. Every LLM call is captured as a trace with full context — inputs, outputs, tool calls, latency, token cost, and metadata. You can drill into any production request, set up alerts on quality degradation, and monitor trends over time without building custom logging.
Yes. Confident AI offers a fully self-hosted deployment option alongside the managed cloud. You can run the entire platform in your own VPC or on-prem infrastructure, keeping all data within your network. Self-hosting is available on our Enterprise plan —
to get started.
Most teams are up and running in under 15 minutes. Install the SDK, add a few lines of code to log traces or run evals, and results show up in the platform immediately.
Yes. DeepEval integrates directly into your CI pipeline so you can run regression tests on every pull request. If quality drops below thresholds you define, the build fails — no bad prompts make it to production.
Confident AI is SOC 2 Type II compliant and offers both cloud and on-prem deployment. All data is encrypted in transit and at rest, and we never use your data to train models.