Braintrust
Evals and observability platform for reliable AI agents
What is Braintrust? Complete Overview
Braintrust is an end-to-end AI development platform designed to help teams build, evaluate, and deploy reliable AI agents. It addresses key challenges in AI development, such as unpredictable agent failures, quality assurance, and performance monitoring. The platform provides tools for iteration, evaluation, and deployment, ensuring that AI features work as intended and improve over time. Braintrust is trusted by leading companies to enhance productivity, accelerate AI feature deployment, and maintain high standards of quality and safety. It is ideal for engineering teams, product managers, and enterprises looking to scale their AI applications with confidence.
What Can Braintrust Do? Key Features
Iterate with Playgrounds
Fast prompt engineering and batch testing allow users to refine prompts, swap models, and edit scorers directly in the browser. Compare traces side-by-side to understand performance changes and optimize workflows efficiently.
Comprehensive Evaluations
Run detailed tests on every prompt change to measure accuracy, consistency, and safety. Automated and human scoring ensures nuanced feedback, helping teams make data-driven decisions and prevent quality regressions.
Production Monitoring
Track live model responses with real-time monitoring and online scoring. Configure alerts for quality thresholds and safety violations, ensuring that only high-quality outputs reach users.
AI-Powered Workflows (Loop)
Loop automates time-intensive tasks like prompt optimization, synthetic data generation, and scorer building. It helps teams hit quality targets faster and focus on building compelling AI applications.
Brainstore
A purpose-built database for AI data, Brainstore enables fast querying, filtering, and analysis of logs and traces. It outperforms traditional databases by 86.6x in full-text search and 2.4x in write latency.
Enterprise-Grade Security
Granular permissions, SOC 2 Type II certification, and hybrid deployment options ensure compliance with strict security and privacy requirements, making Braintrust suitable for large organizations.
Best Braintrust Use Cases & Applications
Prompt Engineering
Teams can use Braintrust to refine prompts and evaluate their effectiveness across hundreds of scenarios. This ensures that the final prompts deliver consistent and high-quality outputs.
Quality Assurance
Braintrust's evals and monitoring tools help prevent bad responses from reaching users by detecting quality drops and triggering alerts for immediate action.
Model Comparison
Compare different models or versions side-by-side to determine which performs better under specific conditions, enabling data-driven decisions for model selection.
Enterprise AI Deployment
Large organizations can deploy AI applications with confidence, knowing that Braintrust's security, compliance, and scalability features meet their stringent requirements.
How to Use Braintrust: Step-by-Step Guide
Sign up for a free account on Braintrust and explore the platform's features. No credit card is required to get started.
Use the playground to experiment with prompts, models, and scorers. Compare different versions side-by-side to identify improvements.
Run evaluations on your AI applications using real or synthetic data. Measure performance metrics and gather feedback from automated and human scorers.
Deploy your AI features to production and monitor their performance in real-time. Set up alerts to detect and address quality or safety issues promptly.
Leverage Loop for automated optimizations and Brainstore for scalable log analysis to continuously improve your AI applications.
Braintrust Pros and Cons: Honest Review
Pros
Considerations
Is Braintrust Worth It? FAQ & Reviews
The Free plan is ideal for individuals or small teams starting with AI development. The Pro plan suits growing teams needing more resources, while Enterprise is for large organizations with custom requirements.
Processed data refers to the volume of data (in GB) that Braintrust analyzes and stores during evaluations and monitoring. It includes logs, traces, and other AI-related data.
Scores are metrics generated during evaluations to measure the performance, accuracy, or quality of AI outputs. They help teams track improvements and identify regressions.
Trace spans are individual units of work recorded during AI operations. They help track the flow of requests and identify performance bottlenecks or errors.
Billing for the Pro plan is monthly, with additional charges for extra data, scores, or retention. Enterprise plans have custom pricing based on specific needs and usage.