Maxim is an end-to-end AI quality platform designed for teams building LLM-powered products and AI agents. It provides tooling for prompt engineering, dataset management, automated evaluation pipelines, and production monitoring. Engineers and product teams can use Maxim to run structured experiments comparing prompts, models, and configurations, then track quality metrics over time as applications move from development to production. The platform supports custom evaluation criteria, human-in-the-loop review workflows, and automated regression testing to catch quality degradations before they reach end users. Maxim also offers observability features that log and trace LLM calls in production, enabling teams to debug failures, analyze latency, and measure output quality at scale. It is positioned as a unified workspace where AI teams can iterate on prompts, validate changes against curated test datasets, and maintain confidence in deployed AI systems without switching between multiple disconnected tools.
Target audience and deployment
- Startup
- SMB
- Mid-market
- Enterprise
- Cloud
- API
Key features
Use cases
- Evaluate LLM outputs against custom quality criteria
- Run prompt experiments and A/B comparisons
- Monitor AI agents and LLM apps in production
- Manage and version test datasets
- Automate regression testing for AI pipelines
- Debug and trace AI agent failures
Best for
- AI engineers who need to systematically test and evaluate LLM-powered applications before deployment
- ML teams who need to monitor production AI agents for quality regressions and failures
- Product teams who need to iterate on prompts and validate changes against curated test datasets
- Engineering leads who need observability and tracing across complex multi-step AI pipelines
Integrations
AI models included
OpenAI, Anthropic, Google Gemini, Mistral, Llama