/

Confident AI

  • What it is:Confident AI is a cloud platform for evaluating, testing, and monitoring large language model applications with metrics, observability tools, and CI/CD integration.
  • Best for:AI/ML engineers testing LLMs, Cost-conscious startups, QA teams needing observability
  • Pricing:Starting from $0/month
  • Rating:85/100Very Good
  • Expert's conclusion:Confident AI is best suited for serious engineering teams looking to establish production-ready LLM quality through its robust capabilities for evaluating, tracing, and automating LLMs.
Visit website
Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Confident AI and What Does It Do?

A confident AI is an open source platform that enables you to test and benchmark your Large Language Model (LLM) applications. The platform provides tools for testing and benchmarking, optimizing and monitoring LLM solutions, and red-teaming LLM solutions. This is achieved through the DeepEval framework which is also open source. The DeepEval framework is used by Engineering Teams from Startups and Enterprises such as Microsoft, BCG, Booking.com, Accenture, Cisco and Toyota. The YC W25 Company uses its expertise to develop AI Solutions of high quality and reliability with excellent metrics and observability.

Active
📅Founded 2025
🏢Private
TARGET SEGMENTS
AI EngineersQA TeamsProduct LeadersEnterprisesStartups

What Are Confident AI's Key Business Metrics?

📊
12k+
GitHub Stars (DeepEval)
📊
3M+
Monthly Downloads (DeepEval)
📊
2M+
Daily Evaluations
📊
5M+
Total Evaluations Run
👥
Booking, Accenture, Cisco, Toyota, Microsoft, BCG
Customers
📊
YC W25
Funding

How Credible and Trustworthy Is Confident AI?

85/100
Excellent

Confident AI is a start-up which has received funding from YC W25. As a relatively new start-up, it does not have a lot of publicly available information regarding financial details. It has a solid technical base due to its successful application of the DeepEval Framework and has been adopted by numerous Enterprise Customers.

BREAKDOWN
Product Maturity75/100
Company Stability80/100
Security & Compliance90/100
User Reviews85/100
Transparency85/100
Support Quality80/100
TRUST SIGNALS
Y Combinator W25DeepEval: 12k GitHub stars, 3M monthly downloadsCustomers: Microsoft, BCG, Booking, Cisco, ToyotaEnterprise compliance standards5M+ total evaluations run

What is the history of Confident AI and its key milestones?

2025

Company Founded

Confident AI was founded by Jeffrey Ip (ex-Google YouTube Infrastructure, ex-Microsoft) and Kritin Vongthongsri (AI Researcher from Princeton University).

2025

Y Combinator W25

Confident AI was accepted into Y Combinator's W25 Batch with a DeepEval-based LLM Evaluation Platform.

2025

Platform Launch

Confident AI launched their Cloud Platform for LLM Evaluation and Observability.

What Are the Key Features of Confident AI?

✨
LLM-as-a-Judge Metrics
Confident AI uses more than 30 Use Case Specific Metrics based on the DeepEval Framework to Quantitatively and Qualitatively Evaluate LLM Solutions.
✨
Production Monitoring
Confident AI continuously monitors the Outputs generated by LLMs and Enriches Datasets with Real World Adversarial Test Cases.
🔗
CI/CD Integration
Confident AI allows users to run Unit Tests and Catch Regressions Directly within CI/CD Pipelines Before Deployment.
✨
Component-Level Testing
Users can Create Customized Metrics Based on Individual Components within the LLM Pipeline to identify Weaknesses.
✨
Collaboration Dashboards
Confident AI provides Non-Technical Team Members with Easy to Use Analytics Dashboards to Review Evaluation Results.
👥
Red-Teaming & Guardrails
Confident AI identifies Inappropriate Behavior and Creates Operational Guardrails to Ensure Safe Production LLM Usage.
✨
Enterprise Compliance
Confident AI complies with Industry Standards for Security in Regulated Industries by Providing Data Residency in both the U.S. and E.U., Project Isolation and Custom Permissions.

What Technology Stack and Infrastructure Does Confident AI Use?

Infrastructure

Cloud platform with US (North Carolina) and EU (Frankfurt) data residency; supports self-hosted AWS/Azure/GCP

Technologies

PythonDeepEvalLLM-as-a-Judge

Integrations

CI/CD PipelinesLLM FrameworksObservability Tools

AI/ML Capabilities

Powered by DeepEval OSS framework with use-case-specific, deterministic LLM evaluation metrics and 30+ LLM-as-a-judge metrics

Based on official website and Y Combinator profile

What Are the Best Use Cases for Confident AI?

AI Engineering Teams
By integrating Best-in-Class Evaluations into CI/CD and Observability Workflows, Confident AI Enables Developers to Accelerate Iteration for Their LLM Apps by up to X10 Faster.
QA & Testing Teams
Using Automated Test Reports, Confident AI Enables Developers to Validate Changes to LLM Performance and Detect Regressions Before Production Deployment.
Product Managers
Confident AI enables Developers to Measure End-to-End Prompt/Model Performance and Track Continuous Improvement of their AI Solutions Through Dashboards.
Regulated Enterprises (Healthcare/Finance)
The level of enterprise compliance that exists regarding data residency options as well as security controls appropriate for mission-critical workflows.
Non-Technical Business Users
Dashboards are intuitive to evaluate insight without requiring either a code view or technical expertise to interpret results.
NOT FORSimple Rule-Based Systems
Overkill for basic validation needs - requires LLM evaluation complexity to be able to justify the use of a platform's capabilities.
NOT FORReal-Time Low-Latency Applications
Evaluation overhead could potentially interfere with meeting the less-than-100ms response time requirement for development/testing phases.

How Much Does Confident AI Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Free$0/month1 project, 5 test runs/week, 1 week data retention, DeepEval reports, evals in dev/CI-CD, LLM tracing, prompt versioning, community support—
Starter$19.99/user/monthAll Free features plus full LLM testing suite, model/prompt scorecards, dataset annotation, custom metrics, online evals, human-in-loop, email support, 20k traces/month/project, 5k eval runs/month, 1 month retention—
Premium$79.99/user/monthAll Starter features plus real-time alerting, dataset backup/revision history, no-code workflows, full API access, priority email support, HIPAA add-on, 75k traces/month/project, 25k eval runs/month, 6 months retention—
TeamPricing based on needsAll Premium features plus custom roles/permissions, HIPAA/SOC2/SSO, dedicated support, feature prioritization, custom data residency/retention/SLAs, 500k traces/month/org, 100k eval runs/month, 6 months retention, min 10 users—
EnterprisePricing based on needsAll Team features plus AI red teaming, infosec review, pen testing, on-prem deployment, 24x7 support, unlimited users/projects/traces/evals, custom retention—
Free$0/month
1 project, 5 test runs/week, 1 week data retention, DeepEval reports, evals in dev/CI-CD, LLM tracing, prompt versioning, community support
Starter$19.99/user/month
All Free features plus full LLM testing suite, model/prompt scorecards, dataset annotation, custom metrics, online evals, human-in-loop, email support, 20k traces/month/project, 5k eval runs/month, 1 month retention
Premium$79.99/user/month
All Starter features plus real-time alerting, dataset backup/revision history, no-code workflows, full API access, priority email support, HIPAA add-on, 75k traces/month/project, 25k eval runs/month, 6 months retention
TeamPricing based on needs
All Premium features plus custom roles/permissions, HIPAA/SOC2/SSO, dedicated support, feature prioritization, custom data residency/retention/SLAs, 500k traces/month/org, 100k eval runs/month, 6 months retention, min 10 users
EnterprisePricing based on needs
All Team features plus AI red teaming, infosec review, pen testing, on-prem deployment, 24x7 support, unlimited users/projects/traces/evals, custom retention

How Does Confident AI Compare to Competitors?

FeatureConfident AILangSmith20 Dollar Eval
Core FunctionalityLLM evaluation, tracing, testingLLM tracing, evaluationLLM evaluation
Starting Price$19.99/user/mo$40/user/mo$20/review or $39/mo
Free TierYes (1 project, 5 runs/wk)Yes (1 seat, 5k traces)
Enterprise FeaturesSSO, HIPAA, SOC2, on-premEnterprise plan
API AvailabilityYes (Premium+)Yes
Data Retention1-6+ months by tier14 days free, more paid
Support OptionsEmail to 24x7 dedicatedStandard support
Security CertificationsSOC2, HIPAA add-onEnterprise compliance
Core Functionality
Confident AILLM evaluation, tracing, testing
LangSmithLLM tracing, evaluation
20 Dollar EvalLLM evaluation
Starting Price
Confident AI$19.99/user/mo
LangSmith$40/user/mo
20 Dollar Eval$20/review or $39/mo
Free Tier
Confident AIYes (1 project, 5 runs/wk)
LangSmithYes (1 seat, 5k traces)
20 Dollar Eval—
Enterprise Features
Confident AISSO, HIPAA, SOC2, on-prem
LangSmithEnterprise plan
20 Dollar Eval—
API Availability
Confident AIYes (Premium+)
LangSmithYes
20 Dollar Eval—
Data Retention
Confident AI1-6+ months by tier
LangSmith14 days free, more paid
20 Dollar Eval—
Support Options
Confident AIEmail to 24x7 dedicated
LangSmithStandard support
20 Dollar Eval—
Security Certifications
Confident AISOC2, HIPAA add-on
LangSmithEnterprise compliance
20 Dollar Eval—

How Does Confident AI Compare to Competitors?

vs LangSmith

While Confident AI is approximately 50 percent less expensive per seat ($19.99 vs $40) it also has a more generous free tier (unlimited seats, 10K traces, 1 month retention vs 1 seat / 5K traces / 14 days). Confident AI does not have seat limitations in its less expensive plans, whereas LangSmith does. Also, while both platforms offer a GB-month based pricing plan at $1/GB-month for both ingestion and retention, Confident AI provides this pricing plan for all of their plans, whereas LangSmith only offers it on some of their plans.

Therefore, I would recommend Confident AI as an option for cost-conscience teams and startups who require enterprise features but do not want seat restrictions.

vs 20 Dollar Eval

While Confident AI offers a complete platform including a full range of tools such as tracing, CI/CD integration, and tiered pricing, LangSmith offers a single price point per review ($20) or a flat rate of $39/month.

For production teams, I would recommend Confident AI. However, I would recommend LangSmith for one-time evaluations.

What are the strengths and limitations of Confident AI?

Pros

  • Because Confident AI’s pricing is transparently based upon the actual amount of usage a customer makes of the service — $1/GB-month — customers will always know exactly what they will pay each month for their usage.
  • Confident AI also offers a generous free tier that includes 1 project, 5 runs/week which should be sufficient for most experimentation purposes.
  • In terms of pricing, Confident AI is 50% cheaper than LangSmith — $19.99 vs $40 per seat for individuals.
  • Like LangSmith, Confident AI allows customers to scale their seat usage at will and there are no limits on how many seats a customer can purchase on any of the less expensive plans offered by Confident AI.
  • Both Confident AI and LangSmith offer enterprise-ready features such as HIPAA, SOC2, on-prem, and custom residency options for customers.
  • Additionally, while both platforms offer some form of data retention, Confident AI allows customers to retain their data for longer periods of time — up to 6+ months — compared to LangSmith which retains data for only 14 days.
  • Customers who wish to try Confident AI prior to purchasing a paid tier need not enter a credit card number and may therefore try the service prior to making a financial commitment to a paid tier.

Cons

  • As part of the free tier offered by LangSmith, customers are allowed only 5 test runs per week and their data will be retained for only 1 week.
  • Unlike Confident AI, LangSmith uses a combination of per user plus usage pricing which could result in higher costs for larger teams.
  • In addition to limiting the number of tests customers may run under their free tier, LangSmith also limits the total number of traces customers may create per month — 20k traces per month per project.
  • While Confident AI mentions it has a free tier, LangSmith does not mention a free trial and only references a free tier with very tight limits.
  • Unfortunately, there appears to be conflicting pricing information available for LangSmith — $19.99 vs $39 — depending on the source.
  • Custom enterprise pricing - transparent for large organizations
  • Young platform - Less mature ecosystem compared to LangSmith

Who Is Confident AI Best For?

Best For

  • AI/ML engineers testing LLMs — Accessible pricing for full test suite, custom metrics, CI/CD integration
  • Cost-conscious startups — 50 percent less expensive than LangSmith, a very generous free tier, YC deal available
  • QA teams needing observability — Tracing, scorecards, real time alerting, data set management
  • Compliance-focused enterprises — Add-on for HIPAA / SOC2, on premises, custom residency/ SLA's
  • Small teams scaling evaluations — Unlimited seats on lower cost plans, flexible usage of GB/month

Not Suitable For

  • One-off evaluators — The subscription model is less ideal than per review pricing such as 20 dollar eval
  • Budget-constrained hobbyists — The free tier has limits (5 runs/wk), consider using fully free OSS tools
  • Very large enterprises needing proven scale — Younger platform compared to other well-established players; consider LangSmith for maturity
  • Teams needing instant unlimited access — Trace/eval run limits are scaled up to your tier; either start with a higher tier or use LangSmith

Are There Usage Limits or Geographic Restrictions for Confident AI?

Free Tier Projects
1 project max
Free Tier Test Runs
5 runs per week
Free Tier Data Retention
1 week
Starter LLM Traces
20k/month per project
Starter Online Eval Runs
5k/month
Starter Data Retention
1 month
Premium LLM Traces
75k/month per project
Premium Online Eval Runs
25k/month
Premium Data Retention
6 months
Team Min Users
Starting from 10 users
Team LLM Traces
500k/month per org
Team Online Eval Runs
100k/month
Enterprise Traces/Evals
Unlimited
Compliance Add-ons
HIPAA available Premium+

Is Confident AI Secure and Compliant?

SOC 2 ComplianceSOC II compliance available in Team tier and above
HIPAA ComplianceHIPAA add-on available in Premium tier and above
Custom Data ResidencyCanada, Australia, Japan etc. available as Team add-on
RBAC & Data MaskingRole-based access control and data masking in Enterprise features
On-Premises DeploymentDedicated on-prem deployment available in Enterprise tier
99.9% Uptime SLAService level agreement for production reliability
Custom Data RetentionFlexible retention policies beyond standard 6 months in higher tiers

What Customer Support Options Does Confident AI Offer?

Channels
Free tierStarter tierPremium tierTeam tierEnterprise tier
Hours
24x7 for Enterprise, business hours for lower tiers
Response Time
Priority response for Premium+, standard email for Starter
Satisfaction
N/A - limited review data available
Specialized
Dedicated technical support with dataset curation assistance in higher tiers
Business Tier
Feature prioritization and custom SLAs for Team/Enterprise
Support Limitations
•Free tier limited to community/documentation only
•No phone support mentioned for any tier
•Dedicated channels Enterprise-only

What APIs and Integrations Does Confident AI Support?

API Type
REST API with endpoints like /v1/metric-collections, /v1/evaluate for running LLM evaluations on test cases, traces, spans, and threads
Authentication
API Key authentication required on every request (CONFIDENT_API_KEY header). Supports Organization-level (manage teams, billing, projects) and Project-level (datasets, prompts, traces) keys. SSO available for Enterprise
Webhooks
No webhook support mentioned in documentation
SDKs
Python (deepeval), TypeScript (deepeval-ts), integrates with LangChain callbacks, AI SDK, and other observability frameworks
Documentation
Good - comprehensive API reference with quickstart examples, authentication guide at confident-ai.com/docs/api-reference
Sandbox
Free account provides access to full platform for testing with quota tracking
SLA
Rate Limits
Usage tracked against quotas per API key, specific limits not detailed in public docs
Use Cases
Run online evaluations, create custom datasets/prompts, human annotations, production tracing, CI/CD regression testing, experiment with prompts/models

What Are Common Questions About Confident AI?

Confident AI is an AI Quality Platform for evaluating Large Language Model (LLM) applications. Evaluate LLM performance using the Evals API by running tests on Datasets, Traces, Spans, Threads or integrate the DeepEval SDK for local testing with cloud based reporting.

A free account is available for the first round of setting up and testing your application. Your usage will be tracked against usage quotas. Also available are Enterprise level features such as Single Sign On (SSO). Contact Sales for custom pricing.

Confident AI provides Comprehensive LLM Evaluation using DeepEval Metrics, whereas LangSmith is focused on General Observability and Debugging. Confident AI has better Regression Testing capabilities along with Human Annotation Workflows.

Stored in US by Default, EU Residency available. Project Isolation provided via API Keys. Enterprise SSO Support ensures you have proper access controls.

Yes, Native Integrations are available. Both LangChain Callback Handler and Vercel AI SDK Telemetry Tracer are supported through the DeepEval Libraries.

Go to app.confident-ai.com to create a free account. Install deepeval, login with api key. Either follow the 5 minute API Quick Start or the Comprehensive Docs.confident-ai.com Guides.

Free account offers the full feature set of the platform, but limited by resource utilization limits. There is no time-bound free trial but is suitable for testing and first-phase production environments.

No publicly disclosed SLAs or usage limits such as webhook are available. All enterprise-focused features require an email to Sales.

Is Confident AI Worth It?

Confident AI's strong foundation in providing an extensive suite of LLM evaluation capabilities via its mature REST API and the DeepEval SDK ecosystem, as well as a strong focus on producing a high-quality production-ready product for AI quality teams that can be easily integrated into CI/CD pipelines, make it a strong contender for large-scale enterprises. Its free-tier will help lower entry barriers while its paid-enterprise features will enable scaling.

Recommended For

  • Development of production LLM applications by AI/ML Engineering Teams
  • Systematic LLM testing and regression test suites for QA teams
  • Companies utilizing LangChain, Vercel AI SDK, or DeepEval-based work flows
  • Teams that need both development experimentation and production monitoring

!
Use With Caution

  • Teams that require sub-second response times for API-based workflow evaluations
  • Companies that require on-premises deployment - cloud-first platform
  • Small teams who have yet to adopt formalized AI quality process

Not Recommended For

  • One-time evaluation needs - open source alternatives are likely to be less expensive
  • Applications that do not utilize LLMs - focused on testing LLMs
  • Budget-constrained Startups that have no production AI applications
Expert's Conclusion

Confident AI is best suited for serious engineering teams looking to establish production-ready LLM quality through its robust capabilities for evaluating, tracing, and automating LLMs.

Best For
Development of production LLM applications by AI/ML Engineering TeamsSystematic LLM testing and regression test suites for QA teamsCompanies utilizing LangChain, Vercel AI SDK, or DeepEval-based work flows

What do expert reviews and research say about Confident AI?

Key Findings

Confident AI provides the following for comprehensive LLM evaluation, which includes traces, datasets, prompts, and human annotations: REST Evals API, DeepEval SDK, strong integrations with LangChain, Vercel AI SDK, Python/TS ecosystems, and a multi-tenant architecture that allows organizations/projects to isolate themselves from each other at scale will allow for enterprise-level adoption, while the free-tier will allow for widespread adoption.

Data Quality

Good - detailed technical documentation from official API reference and developer guides. No pricing/SLA details publicly available. Integrations confirmed through third-party docs (LangChain, AI SDK).

Risk Factors

!
Publicly disclosed uptime/SLO guarantees unavailable
!
Pricing unclear beyond the free tier
!
Only deployed in the cloud with on-prem deployments unsupported
!
Depends on adoption of the DeepEval ecosystem for functionality
Last updated: February 2026

What Are the Best Alternatives to Confident AI?

  • •
    LangSmith: Tracing, Testing, and Monitoring of LangChain's Observability Platform. The LangChain native team will have a broader ecosystem, however it has less to do with evaluating metrics than Confident AI. smith.langchain.com
  • •
    Weights & Biases (W&B Weave): Evaluation of LLM through ML experimentation platform. More robust tracking of experiments, and less robust tracing in production. Research teams may find this useful as well as less of a focus on CI/CD. wandb.ai
  • •
    Phoenix (Arize): Production LLM Monitoring with Open Source. Free Self Hosted option but requires more of your DevOps. Teams looking to avoid vendor lock-in are best suited for this solution. arize.com/phoenix
  • •
    Helicone: Cost Monitoring and Caching of LLM with an Observability Focus. Less expensive and easier to implement but does not provide much for evaluation. Startups that are budget conscious would be best suited for this. helicone.ai
  • •
    OpenLLMetry: Customizable Open Telemetry Based LLM Observability. Very customizable and based on industry wide standards, but difficult to set up. Teams already using their own observability stacks are best suited for this solution. traceloop.com/openllmetry

What Additional Information Is Available for Confident AI?

Open Source Foundation

Uses DeepEval, the Leading Open Source Framework for LLM Evaluation, to enable local development and collaborative development in the cloud. github.com/confident-ai/deepeval

Multi-Language Support

Python (deepeval) and TypeScript (deepeval-ts) SDKs are both available. Also integrates with LangChain Callbacks and Vercel AI SDK Telemetry.

Data Residency Options

Defaults to Hosting in the United States. Data Residency in the European Union is available via setting the CONFIDENT_BASE_URL Environment Variable to https://eu.api.confident-ai.com.

No-Code Access

A Web Application at app.confident-ai.com provides a means for users that do not require the use of an SDK to perform Browser-Based Testing.

What Are Confident AI's Evaluation Metrics?

30+
Metrics Available
17k
Pre-built Evaluations
50+
LLM-as-a-Judge Metrics

What Testing Capabilities Does Confident AI Offer?

A/B Testing

Compare Model and Prompt Performance.

Regression Testing

Identify Quality Degradation in CI/CD Pipelines.

Output Classification

Automatically Classify LLM Outputs.

Multi-turn Evaluation

Automatically Validate Conversation Consistency and Memory.

Component-level Testing

Granularly Debug Agent Components.

How Does Confident AI's Benchmark Support Compare?

BenchmarkCategorySupported
Custom DatasetsAll CategoriesYes
RAG PipelinesRetrieval AugmentedYes
Agent WorkflowsAgentic SystemsYes
Production TracesReal-world UsageYes

What Model Compatibility Does Confident AI Support?

Any LLMOpenAIAnthropicLlamaMistralCustom ModelsRAG PipelinesAI Agents

What Is Confident AI's Evaluation Modes?

Single-turn
Input-output evaluation
End-to-end
Black box AI app testing
Multi-turn
Conversation validation
Component-level
Agent debugging
Production Monitoring
Real-time quality scoring

How Does Confident AI Ensure Safety Through Testing?

Red Teaming

Test Safety Vulnerabilities.

Adversarial Testing

Harden Against Attacks.

Drift Detection

Monitor Drift in Prompt and Quality.

Compliance Testing

Complies with Healthcare/Finance Standards

What Is Confident AI's Ci Cd Integration?

DeepEval SDK
Python framework integration
Unit Testing
CI/CD pipeline support
Live Alerting
Instant quality notifications
API Access
REST API + cloud platform

Expert Reviews

📝

No reviews yet

Be the first to review Confident AI!

Write a Review

Similar Products

Giskard
giskard.ai
Arize AI
arize.com
WhyLabs
whylabs.ai