Hamming Features
Hamming is an AI evaluation and optimization platform that helps engineering teams build reliable and high-quality AI products faster.
View MoreKey Features of Hamming
Hamming is an AI optimization platform that helps engineering teams build reliable and self-improving AI products. It offers automated testing for voice agents, prompt optimization, evaluation of AI outputs, and active monitoring of AI systems in production. The platform enables faster iteration on prompts, retrieval pipelines, and agents while ensuring high-quality, accurate outputs.
Automated Voice Agent Testing: Uses AI-powered voice characters to automatically call and test voice agents, significantly speeding up the testing process.
Prompt Optimizer & Playground: Automatically generates optimized prompts and provides a playground to test LLM outputs on datasets, saving time on manual prompt engineering.
AI Output Evaluation: Measures accuracy, tone, hallucinations, precision and recall of AI outputs using custom evaluations tailored to specific use cases.
Active Monitoring: Tracks and scores how users interact with AI apps in production, flagging cases that need attention and allowing easy conversion of calls into test cases.
Collaboration Features: Supports team collaboration with experiment tracking, manual overrides, dataset versioning, and result sharing capabilities.
Use Cases of Hamming
Healthcare AI Development: Build accurate clinical documentation and medical co-pilot AI apps with reduced risk of errors or hallucinations.
Financial Services AI: Develop reliable AI systems for financial analysis and customer service, ensuring regulatory compliance and accuracy.
Customer Support Automation: Create and optimize AI-powered chatbots and voice agents for improved customer interactions and support.
Content Generation and Moderation: Develop and refine AI systems for generating and moderating content across various platforms with high accuracy.
Pros
Significantly speeds up AI development and testing processes
Helps ensure reliability and accuracy of AI outputs
Supports multiple LLM providers and integrates with existing AI infrastructure
Offers comprehensive tools from development to production monitoring
Cons
May require initial setup and integration effort
Potential learning curve for teams new to AI development tools
Pricing information not readily available, may be costly for smaller teams or projects
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