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Evaluate and improve AI, faster

Agents Developer Deployment

Overview


Explore more AI Agents

Maxim is an end-to-end AI evaluation and observability platform, empowering modern AI teams to ship products with quality, reliability, and speed. Key Features:
  • Experimentation
  • Prompt CMS
  • Prompt IDE
  • Data and tools
  • Visual flows
  • Evaluation
  • Observability
  • Datasets Use Cases:
  • Rapid iteration and testing of prompts
  • Unified framework for evaluation
  • Real-time monitoring and optimization of AI systems
  • Data management and curation for AI teams Benefits:
  • Lightning fast set-up
  • Comprehensive testing
  • Complete customization
  • Framework agnostic
  • Full spectrum support
  • Enterprise ready
  • Collaboration-first
  • Priority support 24*7

    • Capabilities

    • Simulates AI agents across diverse scenarios using AI-powered simulations
    • Evaluates agent quality using predefined and custom metrics
    • Integrates with CI/CD workflows to automate agent testing
    • Simplifies and scales human evaluation pipelines
    • Generates reports to track progress across experiments
    • Supports leading AI stack providers through framework-agnostic design
    • Provides SDKs and CLI for streamlined developer experience
    • Facilitates in-VPC deployment for enhanced security
    • Integrates custom single sign-on (SSO) for enterprise authentication
    • Monitors agents in real-time, including logging and debugging
    • Enhances AI agents' ability to perform complex tasks with Agent Workflow Memory (AWM)
    • Achieves high task success rates in website tasks, such as browsing and content management
    • Reduces average steps per task, increasing efficiency
    • Handles intricate workflows requiring multi-stage decision-making
    • Tests agents at scale across thousands of scenarios
    • Offers a prompt IDE for testing and iterating prompts, prompt versioning, and low-code prompt chains
    • Provides real-time alerts on performance and quality regressions
    • Creates robust datasets for evaluations and fine-tuning

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