MLflow GenAI Evaluation vs Outerbounds
MLflow GenAI Evaluation
mlflow.orgOuterbounds
outerbounds.comSide by side
| Figure | MLflow GenAI Evaluation | Outerbounds |
|---|---|---|
| Price from | Free | $2,499/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 3 |
| Spec score · MLOps Platforms | 7.5 (#13) | 7.7 (#10) |
| Integrations | MLflow Tracing lists integrations with 40+ LLM and agent libraries and frameworks, including OpenTelemetry, LangChain, OpenAI, and Anthropic. | Outerbounds documents Snowflake access and examples for AWS Athena, Amazon SageMaker, and Amazon Bedrock. |
| Purpose | MLflow helps teams measure, improve, and monitor the quality of LLM applications and AI agents from development through production. | Outerbounds provides a managed platform for building and deploying production AI and ML systems in a customer’s cloud. |
Plans
In their own words
MLflow GenAI Evaluation
MLflow GenAI Evaluation is a free, open-source API and UI for measuring, improving, and monitoring LLM applications and AI agents from development through production. Evaluation Datasets centralize test cases, expected answers, and evaluation data. Teams can collect feedback from end users and domain experts, attach it to traces, and retain metadata. Scoring includes LLM-as-a-Judge, custom LLM judges, and code-based scorers; automatic evaluation supports LLM judges but not code-based scorers. Results appear in the MLflow UI with per-record details and comparisons between agent versions. MLflow Tracing records production metrics such as latency and token usage. Integrations are listed for more than 40 LLM and agent libraries and frameworks, including OpenTelemetry, LangChain, OpenAI, and Anthropic. Judge adapters include Anthropic, Bedrock, Google, and xAI. API, self-hosted, and web options are available, with Python SDK support, prompt history and testing, regression runs, safety evaluations, tool-call checks, deployment controls, and optional basic HTTP authentication.
Outerbounds
Outerbounds is a managed platform for building and deploying production AI and machine-learning systems in a customer's cloud. It supports data processing, machine learning, AI applications, and agentic workflows, with orchestration, metadata tracking, monitoring, and production deployment tools. Developers can test code locally before deployment; Starter includes up to three cloud workstations. The platform documents Snowflake access and examples for AWS Athena, Amazon SageMaker, and Amazon Bedrock. Outerbounds says it can deploy in any cloud region in less than 15 minutes. Its free Community plan is built around open-source Metaflow, with infrastructure and security managed by the customer. Starter costs $2,499 a month, billed annually, and includes a 30-day trial. Starter is limited to three compute nodes and three workstations. Enterprise lists unlimited compute and workstations, multi-region deployment, and advanced RBAC, with price available by contacting the provider. Starter and Enterprise list SOC 2 compliance and dedicated support; HIPAA support is stated on the product homepage.