Description
Braintrust is an AI observability platform focused on helping teams build and deploy high-quality AI products. It addresses the unique challenges of monitoring and improving AI systems, which can drift, hallucinate, and regress silently. The platform provides tools to observe production AI, evaluate against expectations, and continuously iterate for better results.
Read More
Braintrust works by allowing users to inspect prompts, responses, and tool calls in real-time. It enables the measurement of quality through evaluations, scoring outputs with LLMs, code, or human input. Users can catch issues early and block bad releases before they reach production. The platform offers features like scalable trace ingestion, live performance monitoring, and automated alerts. It also provides SDKs for various programming languages, including Python, TypeScript, and Go, to facilitate easy integration into existing AI workflows.
Key capabilities include real-time trace inspection, which allows users to drill into tool calls and track latency, cost, and quality. The platform supports automated and human scoring to define what good looks like before shipping. Users can run experiments against real datasets, compare prompts side-by-side, and catch regressions automatically. Braintrust also offers customizable trace views, enabling users to build annotation interfaces tailored to their specific tasks. The platform integrates with various tools and frameworks, ensuring flexibility and ease of use. Braintrust is designed for teams running AI in production, from initial agent development to enterprise-scale deployments.
Braintrust is targeted at engineering, product, and AI teams. It is valuable for those building and deploying AI agents, customer support bots, and other AI-powered applications. The platform's value proposition lies in its ability to improve AI quality, reduce the risk of regressions, and accelerate the development cycle. By providing deep observability and evaluation capabilities, Braintrust helps teams build more reliable and effective AI products.
- CategoryMLOps & Model Deployment
- Pricing ModelContact for Pricing
- DeploymentCloud
- PlatformsWeb
Braintrust AI Observability Platform's Core Features
Real-time trace inspection
Automated and human scoring
Prompt comparison and experimentation
Regression detection in CI
Customizable trace views
SDKs for multiple languages
Scalable trace ingestion
Live performance monitoring
Automations and alerts
Integration with existing AI stacks
Versioned datasets
Full-text search for traces
SOC 2 Type II certified
HIPAA and GDPR compliant
How to use Braintrust AI Observability Platform?
Explore the platform: Review the documentation and available resources.
Integrate the SDK: Use the provided SDKs for your preferred language to start tracing.
Inspect traces: Monitor prompts, responses, and tool calls in real-time.
Define evaluations: Set up evaluations to measure the quality of your AI outputs.
Score outputs: Utilize LLMs, code, or human input for scoring.
Analyze results: Identify and address regressions or performance issues.
Iterate and improve: Continuously refine your AI models based on the insights gained.
Deploy and monitor: Deploy your improved AI and continue monitoring its performance.
Braintrust AI Observability Platform's Use Cases
- AI Agent Monitoring
- Customer Support Bots
- Prompt Engineering
- Regression Testing
- Model Comparison
- Performance Analysis
- Dataset Creation
- Compliance Adherence
