Braintrust vs. OPIK
Opik & Braintrust: LLM Evaluation Platform Comparison
Explore how Opik and Braintrust handle evaluation, observability, and iteration across the AI application lifecycle
Opik vs. Braintrust Feature Comparison
Opik and Braintrust both support teams developing LLM-powered applications, but they are optimized for different workflows. Braintrust emphasizes evaluation-centric development with strong dataset tooling, a polished prompt playground, and collaboration features that support prompt iteration and human-in-the-loop review. Opik is fully open source and builds on similar evaluation foundations, extending functionality to production observability and automated agent optimization, with deep support for tracing, online evaluation, agent workflows, and cost- and latency-aware system improvement across the full AI application lifecycle.
| Feature | Details | Opik | Braintrust |
|---|---|---|---|
| Open Source | Open-source and fully transparent with enterprise scalability |  Yes |  No |
| Observability | |||
| AI Application Tracing | Trace context, model outputs, and tools | Yes | Yes |
| Token & Cost Tracking | Visibility into key metrics | Yes | Partial |
| AI Provider, Framework & Gateway Integrations | Native integrations with model providers & various frameworks | Yes | Yes |
| OpenTelemetry Integration | Native support with OpenTelemetry | Yes | Yes |
| Evaluation | |||
| Custom Metrics | Create your own LLM-as-a-Judge, or criteria-based metrics for evaluation | Yes | Yes |
| Built-In Evaluation Metrics | Out-of-the-box scoring and grading systems | Yes | Yes |
| Multi-modal Evaluation | Evaluation support for image, video and audio within the UI | Yes | Partial |
| Evaluation/ Experiment Dashboard | Interface to monitor evaluation results | Yes | Yes |
| Automated Dataset Expansion | Automatically expand datasets for robust evaluation | Yes | Yes |
| Agent Evaluation | Evaluate complex AI apps and agentic systems | Yes | Partial |
| Evaluation and Human Feedback for Conversations | Track annotator insights & scores in production | Yes | No |
| Annotation Queues | Review and annotate outputs by subject matter experts | Yes | Partial |
| Human Feedback Tracking | Track annotator insights & scores in production | Yes | Yes |
| Production Monitoring | Monitoring for production LLM apps | Yes | Yes |
| Prompt Playground | Test & refine prompts and outputs from LLMs | Yes | Yes |
| Agent Optimization | |||
| Automated Agent Optimization | Automatically refine entire agents & prompts | Yes | No |
| Tool Optimization | Optimize how agents use tools | Yes | No |
| Production | |||
| Online Evaluation | Score production traces and identify errors within LLM apps | Yes | Yes |
| Alerting | Configurable alerts | Yes | Partial |
| TypeScript & JavaScript SDK | Developer SDK for JavaScript and TypeScript | Yes | Yes |
| In-Platform AI Assistant | Embedded assistant to guide workflows | Yes | Yes |
These Are Just the Highlights
Explore the full range of Opik’s features and capabilities in our developer documentation or check out the full repo on GitHub.
Opik’s Advantages
Opik is designed to support the entire lifecycle of AI-powered applications, particularly in production observability and automated system improvements, helping teams go beyond evaluation to run, monitor, and optimize LLM & agentic systems at scale.
Comprehensive Production Observability
Full functionality to automatically capture traces, spans, token counts, cost, and latency without heavy manual setup, making root-cause analysis fast and reliable.
Native Agent and Workflow Support
Built-in support for multi-step agents, agent graph visualization, and thread-level evaluation, helping teams understand complex model interactions.
Automated Optimization Workflows
Native optimization capabilities for prompts, parameters, tools, and multi-objective tradeoffs, reducing the need for manual experimentation loops.
Continuous Online Evaluation
Support for on-demand evaluation in production with built-in alerts and guardrails, helping teams detect regressions and maintain quality over time.
Braintrust’s Advantages
Braintrust is optimized for UI-driven experimentation and collaborative evaluation workflows, giving teams intuitive tools for prompt iteration, dataset management, and human review.
Rich Dataset and Evaluation Tooling
Tooling for dataset versioning, schema builders, and integrated evaluation workflows that streamline batch and structured experimentation.
Polished Interactive Playground
Braintrust’s playground supports saved configurations, structured output schemas, span replay, and greater flexibility in experiment setup from the UI.
Built-in Collaboration Features
With comments, assignments, shared views, and review workflows, Braintrust makes it easier for cross-functional and non-technical users to engage in evaluation and annotation.
In-platform AI Assistant
Braintrust’s integrated AI assistant can help generate dataset samples, analyze traces, and improve prompts directly in the interface, speeding up iteration cycles.
“Opik being open-source was one of the reasons we chose it. Beyond the peace of mind of knowing we can self-host if we want, the ability to debug and submit product requests when we notice things has been really helpful in making sure the product meets our needs.”
Jeremy Mumford
Lead AI Engineer, Pattern
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