Braintrust vs Rhesis AI
Braintrust
braintrust.devRhesis AI
rhesis.aiSide by side
| Figure | Braintrust | Rhesis AI |
|---|---|---|
| Price from | $249/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 2 |
| Spec score · AI LLM Evaluation Tools | 9.2 (#3) | 7.5 (#23) |
| Evaluations | Teams can run experiments against datasets and score outputs with language models, code or human reviewers. | Rhesis runs test sets against an application endpoint, evaluates responses using configured metrics, and records results in test runs. |
| Headquarters | LinkedIn lists San Francisco as Braintrust's headquarters. | Potsdam, Germany |
| Intended users | Braintrust says its platform is for teams running agents in production, from early-stage shipping through enterprise scale. | Rhesis describes itself as built for experts, engineers, and product managers working on AI agents. |
| Product | Braintrust describes itself as an active observability platform for AI agents that helps teams inspect production behavior and improve agent quality. | Rhesis is an open-source collaboration layer that brings domain-expert knowledge into AI agent development. |
| Support | The pricing page lists community support, priority support, and shared Slack channel support across its plans. | The getting-started page points users to in-app support, documentation, a support email, GitHub, and Discord. |
| Tracing | The platform lets users inspect agent traces and tool calls and track latency, cost, and quality in real time. | Rhesis Tracing uses OpenTelemetry to capture LLM calls, tool invocations, and retrieval operations in test or production mode. |
Plans
In their own words
Braintrust
Braintrust is an observability platform for teams running AI agents in production. It lets teams inspect agent traces and tool calls while tracking latency, cost, and quality in real time. Users can evaluate datasets, compare prompts and models, and score outputs with LLMs, code, or human reviewers. Discovery tools surface patterns in production traces to help investigate agent behavior, and the Loop agent can run evaluations, generate test cases, and iterate on prompts autonomously. Braintrust lists native SDKs for Python, TypeScript, Go, Ruby, C#, and more, and its MCP server lets coding agents query logs, run evaluations, and update prompts from an IDE. Security options listed include SSO, RBAC, and hybrid deployment; Braintrust states that it is SOC 2 Type II certified and GDPR and HIPAA compliant. Starter is free, with 1 GB processed data, 10,000 scores, and 14-day retention. Pro costs $249.00 per month; Enterprise pricing is custom.
Rhesis AI
Rhesis AI is an open-source collaboration layer for developing and evaluating AI agents. Domain experts, engineers, and product managers can work in a shared space to review test cases and agent versions, annotate them, and record expectations. Teams can generate test sets from application requirements or constraints, including single-turn prompts and multi-turn conversations, then run them against an application endpoint and evaluate responses using configured metrics. Results are saved in test runs. Rhesis Tracing uses OpenTelemetry to capture language-model calls, tool invocations, and retrieval operations in test or production mode. Evaluation options include offline evaluation, online trace metrics, LLM-as-a-judge, custom metrics, and adversarial red-teaming. Model providers connect through LiteLLM, including cloud and local options such as OpenAI, Anthropic, Google Gemini, Mistral, Ollama, and vLLM. Teams can use DeepEval and Ragas metrics or import Garak probes. A REST API supports test sets, runs, results, and trace inspection for integrations and CI/CD. Rhesis offers managed, Docker-local, and self-hosted use; it says it is developed in Germany and hosted in the EU. Both listed free editions cost $0.