Professional prompt editors utilizing models like GPT-4o, Claude 3 Opus, and Gemini-1.5, along with function call simulation capabilities, enable the creation of diverse projects tailored for various use cases with distinct project members and configurations. Each member can have different access control levels, promoting collaborative prompting and sharing. Users can incorporate multiple image inputs in their messages while having control over individual detail parameters, facilitating easy manipulation of each message. The function call schema editor allows for simulation of function call returns seamlessly, and inline variables in prompts enable the running and comparison of results across different variable groups simultaneously. All sensitive information is secured through RSA-OAEP and AES-256-GCM encryption during both transmission and storage, ensuring privacy and data integrity. With Knit, no edits are ever lost, as all edit history is meticulously saved and can be restored at any moment. The platform is compatible with various models, including OpenAI, Claude, and Azure OpenAI, with plans to expand support for even more models. Almost all API parameters can be adjusted within the prompt editors, allowing users to optimize their prompts effectively and discover the most suitable parameters for their needs. This comprehensive approach ensures a streamlined experience for prompt editing and model interaction, fostering creativity and collaboration across teams.