Traceloop
Uses OpenTelemetry tracing data with generative AI to improve system reliability.
About Traceloop
Traceloop is a cutting-edge LLM reliability platform designed to optimize the performance and reliability of large language models (LLMs) in 2026. Leveraging the power of OpenTelemetry tracing data combined with generative AI, Traceloop transforms the evaluation and monitoring of LLMs into a seamless, continuous feedback loop. This innovative tool empowers development teams to detect and address issues early in the deployment cycle, ensuring that every release is an improvement over the last. Traceloop's unique approach allows for real-time insights into model performance, enabling faster debugging and safer deployments. With a single line of code, teams gain live visibility into prompts, responses, and latency, turning noisy logs into actionable insights. The platform's flexibility allows users to define quality metrics tailored to their specific use cases, making it an invaluable tool for startups and enterprises alike. Traceloop's commitment to open standards and its compatibility with a wide range of tools and environments make it a versatile choice for any organization looking to enhance their AI systems' reliability and performance.
Traceloop Key Features
Continuous Feedback Loop
Traceloop transforms the evaluation and monitoring of LLMs into a continuous feedback loop, allowing teams to catch issues early and improve model quality seamlessly. This feature ensures that each release builds on the last, enhancing reliability and performance over time.
OpenTelemetry Integration
By leveraging OpenTelemetry tracing data, Traceloop provides comprehensive insights into the behavior of LLMs. This integration allows for detailed monitoring of model performance, helping teams identify and address potential issues before they impact users.
Custom Evaluator Training
Traceloop allows users to define quality metrics specific to their use case, annotate real examples, and train custom evaluators. This feature ensures that model outputs are scored according to the specific needs and standards of the user, enhancing the relevance and accuracy of evaluations.
Real-Time Monitoring
With real-time monitoring capabilities, Traceloop tracks model responses, latency, and other performance metrics instantly. This feature enables teams to debug issues quickly and deploy updates safely, ensuring consistent model performance.
Automated Quality Checks
Traceloop runs automated quality checks using built-in metrics for faithfulness, relevance, and safety. These checks are applied to real data, providing a baseline understanding of model quality without the need for manual testing.
Enterprise-Ready Deployment
Designed for scalability, Traceloop can be deployed in the cloud, on-premises, or in air-gapped environments. It is SOC 2 and HIPAA compliant, making it suitable for enterprise-level applications with stringent security requirements.
Open Source SDK - OpenLLMetry
Traceloop includes OpenLLMetry, an open-source SDK that provides transparency and flexibility without vendor lock-in. This feature allows developers to integrate Traceloop with their existing tech stack seamlessly.
Traceloop Pricing Plans (2026)
Free
- Up to 50K spans/month
- Up to 5 seats
- 24 hours data retention
- Monitoring Dashboard
- Evaluation Dashboard
- Limited to 50K spans/month
- Limited data retention
Enterprise
- Unlimited spans
- Unlimited seats
- Custom data retention
- Dedicated Slack support
- SOC 2 compliance
- Pricing requires consultation
Traceloop Pros
- + Enhances LLM reliability and performance with a continuous feedback loop.
- + Real-time monitoring provides instant insights into model behavior.
- + Customizable quality metrics tailored to specific use cases.
- + Seamless integration with existing tech stacks via OpenTelemetry.
- + Enterprise-ready with SOC 2 and HIPAA compliance.
- + Supports a wide range of deployment environments, including air-gapped.
Traceloop Cons
- − Might require initial learning curve for teams new to telemetry data.
- − Free tier has a cap of 50,000 spans per month, which may be limiting for larger projects.
- − Custom evaluator training may require additional setup for complex use cases.
- − Advanced features may be more beneficial for large-scale deployments.
- − Pricing for enterprise tier requires direct consultation, which may delay decision-making.
Traceloop Use Cases
Early Issue Detection
Development teams use Traceloop to identify and address potential issues in LLMs before they reach production. This proactive approach prevents user-facing problems and maintains high model performance.
Custom Quality Metrics
Enterprises define custom quality metrics within Traceloop to align model evaluations with their specific business goals. This customization ensures that model outputs meet the unique standards of the organization.
Real-Time Debugging
Real-time monitoring capabilities allow developers to quickly identify and resolve issues as they occur, minimizing downtime and ensuring a smooth user experience.
Regulatory Compliance
Organizations in regulated industries use Traceloop's SOC 2 and HIPAA compliance features to ensure that their LLM deployments meet necessary security and privacy standards.
Performance Optimization
By continuously monitoring and evaluating model performance, teams can use Traceloop to optimize LLMs for speed and accuracy, enhancing the overall user experience.
Cross-Platform Integration
Developers integrate Traceloop with various platforms and frameworks, such as LangChain and LlamaIndex, to streamline their workflow and enhance model capabilities.
What Makes Traceloop Unique
Continuous Feedback Loop
Traceloop's ability to transform evaluation and monitoring into a continuous feedback loop sets it apart from competitors, ensuring that each release improves upon the last.
OpenTelemetry Integration
The integration with OpenTelemetry provides unparalleled insights into LLM performance, allowing for detailed and accurate monitoring that is not commonly found in other platforms.
Custom Evaluator Training
The ability to train custom evaluators based on specific quality metrics offers a level of customization that is unique to Traceloop, catering to diverse user needs.
Enterprise-Ready Design
Traceloop's SOC 2 and HIPAA compliance, along with its deployment flexibility, make it uniquely suited for enterprise applications requiring high levels of security and scalability.
Who's Using Traceloop
Enterprise Teams
Enterprise teams use Traceloop to ensure that their LLM deployments are reliable, secure, and compliant with industry standards. The platform's scalability and customization options make it ideal for large-scale applications.
Startups
Startups leverage Traceloop's ease of use and rapid deployment capabilities to quickly iterate on LLM models, ensuring that they can compete effectively in fast-paced markets.
Data Scientists
Data scientists use Traceloop to gain insights into model performance and behavior, allowing them to fine-tune algorithms and improve model accuracy and relevance.
Developers
Developers integrate Traceloop into their existing tech stack to enhance monitoring and debugging processes, ensuring that LLMs perform optimally in production environments.
How We Rate Traceloop
Traceloop vs Competitors
Traceloop vs Lisapet.ai
Lisapet.ai focuses on AI-driven testing and monitoring, similar to Traceloop, but lacks the deep integration with OpenTelemetry that Traceloop offers.
- + Real-time monitoring
- + Custom quality metrics
- + OpenTelemetry integration
- − Lisapet.ai may offer more specialized testing features
- − Potentially lower cost for basic monitoring needs
Traceloop Frequently Asked Questions (2026)
What is Traceloop?
Traceloop is an LLM reliability platform that uses OpenTelemetry tracing data and generative AI to enhance system reliability.
How much does Traceloop cost in 2026?
Traceloop offers a Free tier with up to 50K spans per month, and Enterprise pricing is available upon consultation.
Is Traceloop free?
Yes, Traceloop offers a Free tier with up to 50,000 spans per month and no seat limit.
Is Traceloop worth it in 2026?
Traceloop is worth it for organizations seeking to improve LLM reliability and performance with real-time insights and customizable metrics.
Traceloop vs competitors in 2026?
Traceloop offers unique features like real-time monitoring and custom quality metrics, setting it apart from competitors.
How to get started with Traceloop?
Start by signing up for a free account and integrate Traceloop with one line of code for live visibility.
What platforms does Traceloop support?
Traceloop supports integration with Python, TypeScript, Go, Ruby, and various frameworks and providers.
Is Traceloop safe and secure?
Yes, Traceloop is SOC 2 and HIPAA compliant, ensuring data privacy and security.
Who should use Traceloop?
Traceloop is ideal for startups, enterprises, research labs, and any organization looking to enhance AI model reliability.
What's new in Traceloop 2026?
Traceloop continues to enhance its real-time monitoring capabilities and integration options.
How does Traceloop compare to alternatives?
Traceloop's focus on real-time insights and custom metrics makes it a strong contender in the LLM reliability space.
Traceloop Search Interest
Search interest over past 12 months (Google Trends) • Updated 2/2/2026
Traceloop on Hacker News
Traceloop Company
Traceloop Quick Info
- Pricing
- Freemium
- Upvotes
- 41
- Added
- January 3, 2026
Traceloop Is Best For
- Technology startups looking to enhance AI model reliability.
- Enterprise IT departments requiring secure, compliant AI solutions.
- AI research labs seeking real-time insights into model performance.
- Software development firms integrating AI into CI/CD pipelines.
- Healthcare organizations maintaining compliance with AI systems.
Traceloop Integrations
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