Agentifact assessment — independently scored, not sponsored. Last verified Mar 6, 2026.
Braintrust
AI observability and evaluation platform for production LLM systems. Runs experiments against datasets with automated scorers (LLM-as-judge, factuality, code-based), tracks regressions in CI/CD via GitHub Actions, and provides real-time production tracing. Multi-language SDKs (Python, TypeScript, Go, Ruby, C#). SOC 2 Type II, HIPAA, GDPR compliant. Free tier with paid plans from $249/month.
Solid choice for most workflows
You're shipping LLM agents to production but have no visibility into why they fail—hallucinations, regressions, and quality drift happen silently between releases.
Traces load in seconds even with thousands of production logs (Brainstore is 80x faster than traditional data warehouses on AI workloads). Annotation workflows let PMs and domain experts flag issues directly in the trace viewer without touching JSON. The workflow is opinionated—production traces → eval datasets → CI checks → continuous improvement—which saves time if your team aligns with it. Expect 50KB average span size (vs. 900 bytes in traditional observability); the platform handles 10GB+ traces where legacy tools break at 100MB.
Your team (engineers, PMs, domain experts) can't collaborate on improving AI quality because debugging happens in isolation—traces are opaque JSON, evals live in notebooks, and there's no shared ground truth.
Cross-functional teams can review and correct traces in the same UI where evals run, eliminating the 'throw it over the wall' pattern. The Loop agent (AI-assisted optimization) can auto-generate better prompts and scorers based on your annotations. Expect a learning curve for non-engineers on the trace viewer, but the interface is designed to be accessible.
You need to measure whether your LLM changes actually improve quality in production, not just in toy examples—but you can't afford to wait for user feedback or manual review at scale.
Real-time quality monitoring with sub-second query latency on large datasets. You can compare prompt/model changes side-by-side in the Playground with quality scores and cost analysis. The platform is framework-agnostic (works with LangChain, Vercel AI SDK, Google ADK, LlamaIndex, etc.), so no vendor lock-in. Expect to invest time tuning scorers—LLM-as-judge is powerful but requires good rubrics.
Scorer quality depends on your rubrics and LLM choice
LLM-as-judge scorers are only as good as the prompt and model you choose. Poorly written rubrics or weak models (e.g., older GPT versions) will produce noisy signals, leading to false positives/negatives in CI checks and misleading production alerts. You need domain expertise to define what 'good' looks like.
Trace volume and cost accumulation
Braintrust captures exhaustive traces (50KB average span size). In high-volume production (millions of requests/day), trace storage and query costs can grow quickly. The platform is designed to scale, but you should monitor ingestion volume and set retention policies early. Use the AI Proxy with caching to reduce redundant trace ingestion.
Trust Breakdown
What It Actually Does
Braintrust helps teams test AI applications against real data, automatically catch quality drops, and monitor production performance—all in one dashboard that integrates with your development workflow.
AI observability and evaluation platform for production LLM systems. Runs experiments against datasets with automated scorers (LLM-as-judge, factuality, code-based), tracks regressions in CI/CD via GitHub Actions, and provides real-time production tracing. Multi-language SDKs (Python, TypeScript, Go, Ruby, C#).
SOC 2 Type II, HIPAA, GDPR compliant. Free tier with paid plans from $249/month.
Fit Assessment
Best for
- ✓llm-tracing
- ✓llm-evaluation
- ✓prompt-management
- ✓monitoring
Not ideal for
- ✗rate limit under burst load
Connection Patterns
Blueprints that include this tool:
Known Failure Modes
- rate limit under burst load
Score Breakdown
Protocol Support
Capabilities
Governance
- permission-scoping
- audit-log
- role-based-access-control
- data-encryption
- api-key-scoping