Competitors
50
Summary
Ask questionsComet provides an end-to-end model evaluation platform for AI developers, offering LLM evaluations, experiment tracking, and production monitoring. Its Opik product focuses on LLM observability and agent optimization, enabling users to test, debug, and improve LLM-powered applications and agents.
Features9/13
See all9/13
Must Have
5 of 5
Conversational AI
API Access
Safety & Alignment Framework
Fine-Tuning & Custom Models
Enterprise Solutions
Other
4 of 8
Code Generation
Multimodal AI
Research & Publications
Security & Red Teaming
Image Generation
Synthetic Media Provenance
Threat Intelligence Reporting
Global Affairs & Policy
PricingFreemium
See allFreemium
Free
$0.00 monthly
- Unlimited team members
- LLM tracing
- Datasets and experiments
- LLM-as-a-judge metrics
- 25k spans per month
- 60-day data retention
Pro
$39.00 monthly
Popular- Pay-as-you-go pricing for: Additional monthly spans, Longer data retention
- LLM tracing
- Datasets and experiments
- LLM-as-a-judge metrics
- 100k spans per month
- 60-day data retention
Enterprise
Custom
- Flexible deployments
- Service accounts and view-only users
- Single sign on
- Dedicated support and SLAs
- SOC 2, ISO 27001, ISO 9001, HIPAA, and GDPR compliance
- LLM tracing
- Datasets and experiments
- LLM-as-a-judge metrics
- Unlimited spans
- Custom data retention
Rationale
Comet ML, particularly through its Opik product, directly addresses several 'must-have' features. It offers LLM evaluation and tracing, which aligns with conversational AI and API access for integrating these capabilities. The platform also emphasizes 'GenAI Guardrails' and 'Maximize Trust & Safety With Guardrails', indicating a focus on safety and alignment. While not explicitly 'fine-tuning', the 'Automate prompt engineering and turn LLM tuning into a repeatable, scalable process' suggests a form of model adaptation. Enterprise solutions are clearly offered with dedicated plans and features like SSO, flexible deployments, and compliance. Additionally, the platform supports code generation through its integrations with various ML frameworks and provides tools for research and publications through its documentation and blog. Security and red teaming are implied through its guardrail features and enterprise-grade security offerings.
