Comet
Experiment tracking evaluation and AI observability for ML teams, available as free cloud or self hosted OSS with enterprise options for secure collaboration.
Pricing Free / Contact sales
Category data
Difficulty Beginner
Type Web App
Status Active
DataRobot
Enterprise AI platform for building governing and operating predictive and generative AI with tools for data prep modeling evaluation deployment monitoring and compliance.
Pricing Contact sales
Category data
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Comet
experiment-trackingevaluationobservability
Shared
mlopsgovernance
Only in DataRobot
monitoringautomationrag
Key Features
Comet
- • One line logging: Add a few lines to notebooks or jobs to record metrics params and artifacts for side by side comparisons and reproducibility
- • Evals for LLM apps: Define datasets prompts and rubrics to score quality with human in the loop review and golden sets for regression checks
- • Observability after deploy: Track live metrics drift and failures then alert owners and roll back or retrain with evidence captured for audits
- • Governance and privacy: Use roles projects and private networking to meet policy while enabling collaboration across research and product
- • Open and flexible: Choose free cloud or self hosted OSS with APIs and SDKs that plug into common stacks without heavy migration
- • Dashboards for stakeholders: Build views that explain model choices risks and tradeoffs so leadership can approve promotions confidently
DataRobot
- • Automated modeling that explores algorithms with explainability so non specialists get strong baselines without custom code
- • Evaluation and compliance tooling that runs bias and stability checks and records approvals for regulators and auditors
- • Production deployment for batch and real time with autoscaling canary testing and SLAs across clouds and private VPCs
- • Monitoring and retraining workflows that track drift data quality and business KPIs then trigger retrain or rollback safely
- • LLM and RAG support that adds prompt tooling vector options and guardrails so generative apps meet enterprise policies
- • Integrations with warehouses lakes and CI systems to fit existing data stacks and deployment patterns without heavy rewrites
Use Cases
Comet
- → Hyperparameter sweeps: Compare runs and pick winners with clear charts and artifact diffs for reproducible results
- → Prompt and RAG evaluation: Score generations against references and human rubrics to improve assistant quality across releases
- → Model registry workflows: Track versions lineage and approvals so shipping teams know what passed checks and why
- → Drift detection: Monitor production data and performance so owners catch shifts and trigger retraining before user impact
- → Collaborative research: Share projects and notes so scientists and engineers align on goals and evidence during sprints
- → Compliance support: Maintain histories and approvals to satisfy audits and customer reviews with minimal manual work
DataRobot
- → Stand up governed prediction services that meet SLAs for ops finance and marketing teams with clear ownership and approvals
- → Consolidate ad hoc notebooks into a managed lifecycle that reduces risk while keeping expert flexibility for advanced users
- → Add guardrails to LLM apps by tracking prompts context and outcomes then enforce policies before expanding to more users
- → Replace fragile scripts with monitored batch scoring so decisions update reliably with alerts for stale or anomalous inputs
- → Accelerate regulatory reviews by exporting documentation that shows data lineage testing and sign offs for each release
- → Migrate legacy models into a common registry so maintenance and monitoring become consistent across languages and tools
Perfect For
Comet
ml engineers data scientists platform and research teams who want reproducible tracking evals and monitoring with free options and enterprise governance when needed
DataRobot
chief data officers ml leaders risk owners analytics engineers and platform teams at regulated or at scale companies that need governed ML and LLM operations under one platform
Capabilities
Comet
Experiments and Artifacts Professional
Prompts and Rubrics Professional
Production Drift Professional
Roles and Private Networking Enterprise
DataRobot
Model Blueprints Professional
Deploy and Scale Enterprise
Monitor and Retrain Enterprise
Governance and Docs Enterprise
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