LLM Beefer Upper logo

LLM Beefer UpperAutomate chain of thought with multi-agent prompt templates

Simplify automating critique, reflection, and improvement, aka getting the model to 'think before it speaks', for far superior results from generative AI. Choose from pre-built multi-agent templates or create your own with the help of Claude Sonnet 3.5.

LLM Beefer Upper screenshot
More About LLM Beefer Upper

LLM Quality Beefer-Upper

Boost Your LLM Productivity

Key Features

  • Automated Critique and Improvement: Enhance LLM responses by automating critique, reflection, and improvement.
  • Chain of Thought: Utilize the proven method to significantly improve LLM quality and accuracy.
  • Custom and Pre-built Templates: Access and refine multi-agent prompt templates for common tasks.
  • Multi-Agent Prompt Drafts: Generate drafts for custom templates using AI.
  • PDF Extraction: Upload knowledge text for agents to process.

Use Cases

  • Content Creation: Improve the quality of generated content for blogs, articles, and marketing materials.
  • Customer Support: Enhance automated responses for customer service applications.
  • Educational Tools: Develop high-quality educational content and tutoring aids.
  • Research Assistance: Generate and refine research summaries and reports.
  • Business Communications: Improve the clarity and effectiveness of business emails and documents.

Pricing

  • Burger (2 credits, ~£0.23): 1 additional LLM agent to review and improve the first output.
  • Ribs (3 credits, ~£0.35): 2 additional LLM agents, one to critique and suggest improvements, and one to re-write the response.
  • Steak (5 credits, ~£0.58): Highest quality with 3 additional LLM agents, one to critique, one to suggest improvements, and one to re-write taking on board the previous agents' comments.

Teams

The LLM Quality Beefer-Upper team is dedicated to maximizing the output quality of language models. By leveraging the best LLM on the market, Claude Sonnet 3.5 API, the team ensures that users receive the highest quality responses. The focus is on continuous improvement and adaptation to new and better models as they become available.