Introduction - re-factor.ai

Key Components

Re-Factor is designed to enable business teams, data scientists, and engineers robustly design, evaluate, and subsequently implement AI within their business processes. We have a few core concepts that will help you make best use of the platform.

Component	Description	Key Features
Resource	Our general term for any piece of unstructured or structured data your AI-driven processes will utilize. This can include documents of any type, webpages, emails, and more.	Resource Repository
LLM	A LLM is an AI model that is capable of generating text based on a prompt or context. LLMs are used in various forms of AI-driven business processes.	Integrations with LLM Providers
Prompt	A prompt is the vehicle for delivering context, instructions, and embedded resources to a large language model.	Runnable Studio
Tool	A tool is an interface to an external system. Tools provide a means for your LLM to access external resources, enabling LLMs to go beyond generating text and perform real work.	Tool Registry, Tool Designer
Completion	A completion is the basic unit of response from an LLM and can be used to generate text or structured data.	Runnable Studio, Runnable API, Runnable Dashboard
Flow	A flow is a workflow that executes a series of tasks in the form of prompts and tool calls. Flows give you a way to exert finer control over sensitive or costly processes.	Runnable Studio, Runnable API, Runnable Dashboard
Agent	An agent is a highly intelligent AI that is capable of choosing in real time the prompts and tools to use to achieve a desired outcome.	Runnable Studio, Runnable API, Runnable Dashboard
Evaluation	An evaluation is an assessment of specific characteristics of the outputs of your AI-driven actions in your processes.	Laboratory, Experiment Log
Experiment	An experiment is a vehicle for comparing the performance of different configurations of a prompt, flow, or agent with one another in order to optimize their performance.	Laboratory, Experiment Log

Using re-factor

We’ve been building AI-enhanced business processes for over a decade. In the LLM era, we AI-driven business process automation has one key challenge: the studio environments for building are unproductive and hard to use. So we designed re-factor to solve everything broken about the current paradigm. Our workflow:

Craft a prompts, flows, and/or agents in the Re-Factor Workbench
Experiment with different instructions, models, parameters, and more to achieve the lowest latency and cost with the highest accuracy for your workflow.
Deploy your prompts, flows, and agents to into productive use via our SDK or API.
Observe the behavior of your prompts, flows, and agents in production to ensure accuracy and cost-efficiency.
Iterate on your prompts, flows, and agents to continuously improve accuracy and cost-efficiency with assistance from re-factor AI.

Why choose re-factor

We find Re-Factor is best for teams that have a few key goals while developing their AI business processes.

You want total control over every aspect of your prompts, model selection, tool registry, and more.
You need robust evaluations, versioning, and deployment slots to ensure accuracy in production and continuous improvement.
You want a dedicated design tool that enables you to iterate far faster to get to production.

API Documentation

View our API Reference to learn how to build with re-factor

Join the Community

Find us on Discord to connect with other builders, get help, and give feedback.

​Key Components

​Using re-factor

​Why choose re-factor

API Documentation

Join the Community

Key Components

Using re-factor

Why choose re-factor