Alert on monitored traces
Inspect every trace in production, monitor quality and latency over time, and get notified immediately when regressions or incidents occur.
Backed byY Combinator
The AI quality platform without the engineering overhead
Turn traces into datasets, datasets into evals, evals into experiments. No code required — ship better AI with every release.
TRUSTED BY 500+ LEADING AI COMPANIES
Evals ran to date[ 0+ ]
THE ROI
Move fast without breaking your AI.
Most teams ship AI without knowing when it will break. We show you failures, regressions, and edge cases before your users ever see them.
“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.”
Sean AustinChief AI Officer, Humach
WHO WE SERVE
Where product, QA, and engineering align.
Confident AI gives organizations an easy way for teams of different backgrounds to monitor AI apps, build datasets, and run AI evals in one simple workflow.
LLM Tracing
Trace UUID 6d63ad3c-8083-fa75-93dd-82e36b52996a
TRACE TREE6d63ad3c-8083-fa75-93dd-82e36b52996a
ics_orchestratorAGENT23.52s
ops_analyst_agentAGENT10.41s
gen_dynamics_knowledgeFUNC2.10s
gen_response_w_tracingLLM8.31s
net_ops_lookupTOOL2.08s
net_ops_lookupTOOL1.87s
ops_report_formatterFUNC12.84s
gen_response_w_tracingLLM
INPUT
How can I improve my credit score from 670 to 700?
OUTPUT
Improving your credit score from 670 to 700 is definitely achievable with some focused efforts. Here are several strategies you can implement to help boost your score:
- Check Your Credit Report — Obtain a free copy from each of the three major credit bureaus at AnnualCreditReport.com.
- Pay Bills On Time — Payment history is the largest factor in your credit score.
TOTAL LATENCY
23.52s
LLM CALLS
1
TOOL CALLS
2
TOTAL TOKENS
2,050
COST
$0.038
PRODUCT FEATURES
Workflows to love, not tolerate.
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.
API AUTOMATIONSAutomate your LLMOps pipeline.
Automate your LLMOps pipeline.
Total control, back to you.
Looking to enable Confident AI for your organization? Our APIs give you the ability to automate everything, from prompts to even building your own custom dashboards.
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")1
INSTALL DEEPEVAL.
Whatever framework you're using, just install DeepEval.
2
CHOOSE METRICS
Whatever framework you're using, just install DeepEval.
3
PLUG IT IN
Decorate your LLM app to apply your metrics in code.
4
RUN AN EVALUATION
Generate test reports to catch regressions and debug with traces.
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.
INTEGRATIONStay In Your Stack.
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
COMMUNITY
The Future of Quality AI Depends on You.
Join the largest and fastest growing community on AI evaluation.
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 — book a demo 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.