Confident AI vs Traceloop: Observability, Prompts & Evals Comparison
Compare Confident AI and Traceloop side by side. Both are tools in the Observability, Prompts & Evals category.
The short answer
Choose Confident AI if built on popular open-source DeepEval framework with strong community (10,000+ GitHub stars).
Choose Traceloop if acquired by ServiceNow for $60-80M providing strong financial backing and integration opportunities.
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Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Open Source | open-source |
| Best For | Developers who want to add automated LLM evaluation testing to their CI/CD pipeline | Teams already using Datadog/Splunk wanting LLM observability |
| Website | confident-ai.com | traceloop.com |
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Pros & Cons: Confident AI vs Traceloop
- +Built on popular open-source DeepEval framework with strong community (10,000+ GitHub stars)
- +Comprehensive evaluation with 30+ LLM-as-a-judge metrics out of the box
- +Y Combinator-backed with proven enterprise compliance (HIPAA, SOC 2)
- +Affordable pricing starting at $29.99/user/month with free tier available
- +Active community with 2,500+ Discord members and strong documentation
- −Small team of 7 employees may limit support capacity
- −Recently founded in 2024, platform may lack maturity of older competitors
- −Per-user pricing model can become expensive for larger teams
- +Acquired by ServiceNow for $60-80M providing strong financial backing and integration opportunities
- +Built on OpenTelemetry standards with open-source OpenLLMetry SDK
- +Recognized as Gartner Cool Vendor demonstrating industry validation
- +One-line code integration for quick setup and deployment
- +Enterprise-ready with SOC 2, HIPAA compliance and multiple deployment options
- −ServiceNow acquisition may lead to platform changes, pricing adjustments, or strategic shifts
- −Small team of 9 employees may be absorbed into larger ServiceNow organization affecting support
- −Limited transparent pricing information following acquisition
- −Uncertainty around long-term product roadmap under new ownership
When to Choose Confident AI vs Traceloop
- Unit testing LLM applications
- Automated evaluation in CI/CD pipelines
- Benchmarking across model versions
About Confident AI
Confident AI is a Y Combinator-backed AI quality platform that enables engineers, QA teams, and product leaders to build reliable AI systems through comprehensive LLM evaluation and observability capabilities. The platform combines 30+ LLM-as-a-judge metrics for testing and validation with real-time production alerts and tracing capabilities. Teams can perform component-level analysis to evaluate individual pipeline components granularly, integrate regression testing into CI/CD pipelines to prevent LLM performance degradation, and leverage built-in dataset management tools for curation and editing. The platform is built on top of the popular open-source DeepEval framework with 10,000+ GitHub stars and 100,000+ monthly documentation reads. Confident AI offers enterprise-grade features including HIPAA and SOC 2 compliance, multi-data residency in US and EU, RBAC controls, 99.9% uptime SLA, and on-premises deployment options.
About Traceloop
Traceloop is an observability and quality assurance platform designed to help teams ship LLM applications 10x faster by transforming evaluation data into continuous feedback loops. The platform enables developers to monitor, test, and improve large language model applications throughout their lifecycle. Built on OpenTelemetry and shipping with OpenLLMetry (their open-source SDK), Traceloop provides real-time monitoring with just one line of code, giving live visibility into prompts, responses, latency, and more. The platform offers built-in quality evaluations for faithfulness, relevance, and safety that automatically apply to production data, along with custom evaluators that users can define and train on annotated examples. Traceloop features automated quality gates that run evaluations automatically on pull requests and in real-time during app execution, plus LLM drift detection to catch performance degradation before it reaches users. The platform supports 20+ LLM providers including OpenAI, Anthropic, Gemini, Bedrock, and Ollama, and integrates with popular frameworks like LangChain, LlamaIndex, and CrewAI. In March 2026, Traceloop was acquired by ServiceNow for $60-80 million, marking the third Israeli acquisition by ServiceNow in under three months. The platform is SOC 2 and HIPAA compliant with cloud, on-premises, and air-gapped deployment options. Traceloop has been recognized as a Gartner Cool Vendor and serves notable clients including HiBob, Target, Miro, IBM, and Babbel.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
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